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Son J, Kim ES, Lee YJ, Lee NW, Ha IH. Minimum clinically important difference and substantial clinical benefit in patients with chronic temporomandibular disorders. J Oral Rehabil 2024. [PMID: 38706163 DOI: 10.1111/joor.13717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 05/07/2024]
Abstract
BACKGROUND Research on temporomandibular disorder (TMD) responsiveness is scarce and limited regarding patients' representativeness. OBJECTIVE(S) This study aimed to estimate minimum clinically important difference (MCID) and substantial clinical benefit (SCB) among a large and diverse patient population regarding sex and age. METHODS In this study, 162 patients participated from five hospitals. MCID and SCB in pain, functional disability and quality of life were examined with anchor-based methods. Patients' global impression of change was used as the anchor. Area under the curve (AUC) values were determined for testing accuracy. Changes from baseline and coefficient of variation by responsiveness status were calculated to explain the results of accuracy. RESULTS SCB was estimated to be 2.18 for the numeric rating scale (NRS) for pain (AUC: 0.80 [95% CI: 0.72-0.88]) in all patients and 2.50 in women (AUC: 0.81 [95% CI: 0.71-0.89]). The estimated SCB of NRS for discomfort (1.50) and Jaw Functional Limitation Scale for mastication (1.35) had wide CIs for AUCs. Likewise, the estimated MCIDs of NRS for pain (0.80) and NRS for discomfort (1.50) had wide CIs for AUCs. Among non-responders who did not achieve the MCID of NRS for pain, the coefficient of variation was very high for all outcomes other than the NRS for pain. CONCLUSION This study investigated the responsiveness of patients with TMD using a large and diverse patient sample. SCB in pain decrease can be used to assess the responsiveness of patients with TMD. Composite outcomes should be developed to estimate MCID.
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Affiliation(s)
- Jaemin Son
- Jaseng Hospital of Korean Medicine, Seoul, Republic of Korea
| | - Eun-San Kim
- Jaseng Spine and Joint Research Institute, Jaseng Medical Foundation, Seoul, Republic of Korea
| | - Yoon Jae Lee
- Jaseng Spine and Joint Research Institute, Jaseng Medical Foundation, Seoul, Republic of Korea
| | - Nam-Woo Lee
- Department of Korean Rehabilitation Medicine, Graduate School, Kyung Hee University, Seoul, Republic of Korea
| | - In-Hyuk Ha
- Jaseng Spine and Joint Research Institute, Jaseng Medical Foundation, Seoul, Republic of Korea
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Heo H, Shin Y, Son J, Ryu S, Cho K, Kim S. Gate-bias stability of triple-gated feedback field-effect transistors with silicon nanosheet channels. Nanotechnology 2024; 35:275203. [PMID: 38579689 DOI: 10.1088/1361-6528/ad3b04] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 04/05/2024] [Indexed: 04/07/2024]
Abstract
In this study, we investigate the gate-bias stability of triple-gated feedback field-effect transistors (FBFETs) with Si nanosheet channels. The subthreshold swing (SS) of FBFETs increases from 0.3 mV dec-1to 60 and 80 mV dec-1inp- andn-channel modes, respectively, when a positive bias stress (PBS) is applied for 1000 s. In contrast, the SS value does not change even after a negative bias stress (NBS) is applied for 1000 s. The difference in the switching characteristics under PBS and NBS is attributed to the ability of the interface traps to readily gain electrons from the inversion layer. The switching characteristics deteriorated by PBS are completely recovered after annealing at 300 °C for 10 min, and the characteristics remain stable even after PBS is applied again for 1000 s.
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Affiliation(s)
- Hyojoo Heo
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Yunwoo Shin
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Seungho Ryu
- Department of Semiconductor System Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Sangsig Kim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
- Department of Semiconductor System Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
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Son J, Lee SH. IgG4-related pericarditis. QJM 2024; 117:300-301. [PMID: 38113430 DOI: 10.1093/qjmed/hcad284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Indexed: 12/21/2023] Open
Affiliation(s)
- J Son
- Division of Cardiology, Department of Internal Medicine, Jeonbuk National University Medical School, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - S H Lee
- Division of Cardiology, Department of Internal Medicine, Jeonbuk National University Medical School, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
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Son J, Jeon J, Cho K, Kim S. Generation and Storage of Random Voltage Values via Ring Oscillators Comprising Feedback Field-Effect Transistors. Nanomaterials (Basel) 2024; 14:562. [PMID: 38607097 PMCID: PMC11013403 DOI: 10.3390/nano14070562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 03/20/2024] [Accepted: 03/21/2024] [Indexed: 04/13/2024]
Abstract
In this study, we demonstrate the generation and storage of random voltage values using a ring oscillator consisting of feedback field-effect transistors (FBFETs). This innovative approach utilizes the logic-in-memory function of FBFETs to extract continuous output voltages from oscillatory cycles. The ring oscillator exhibited uniform probability distributions of 51.6% for logic 0 and 48.4% for logic 1. The generation of analog voltages provides binary random variables that are stored for over 5000 s. This demonstrates the potential of the ring oscillator in advanced physical functions and true random number generator technologies.
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Affiliation(s)
| | | | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea; (J.S.); (J.J.)
| | - Sangsig Kim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea; (J.S.); (J.J.)
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Han J, Son J, Ryu S, Cho K, Kim S. Binary and ternary logic-in-memory using nanosheet feedback field-effect transistors with triple-gated structure. Sci Rep 2024; 14:6446. [PMID: 38499697 PMCID: PMC10948861 DOI: 10.1038/s41598-024-57290-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 03/16/2024] [Indexed: 03/20/2024] Open
Abstract
In this study, we demonstrate binary and ternary logic-in-memory (LIM) operations of inverters and NAND and NOR gates comprising nanosheet (NS) feedback field-effect transistors (FBFETs) with a triple-gated structure. The NS FBFETs are reconfigured in p- or n-channel modes depending on the polarity of the gate bias voltage and exhibit steep switching characteristics with an extremely low subthreshold swing of 1.08 mV dec-1 and a high ON/OFF current ratio of approximately 107. Logic circuits consisting of NS FBFETs perform binary and ternary logic operations of the inverters and NAND and NOR gates in each circuit and store their outputs under zero-bias conditions. Therefore, NS FBFETs are promising components for next-generation LIM.
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Affiliation(s)
- Jongseong Han
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Seungho Ryu
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Sangsig Kim
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.
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Son J, Park H, Yoon E, Kim JI, Choi CH. Development of Novel Focal Irradiation Tool for High-Precision Irradiation Using Clinical Brachytherapy System. Int J Radiat Oncol Biol Phys 2023; 117:e655-e656. [PMID: 37785945 DOI: 10.1016/j.ijrobp.2023.06.2085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Several small animals, including mice, are used to conduct research on state-of-the-art radiation therapy techniques or treatment-related toxicity. However, it is difficult to conduct the focal irradiation to a shallow depth on small animals, because irradiation using LINAC has limitations in energy and field size. The purpose of this paper was to develop a focal irradiation tool for high-precision irradiation and to evaluate beam characteristics. MATERIALS/METHODS We designed the collimator of 1 mm diameter consisting of tungsten material for high-precision irradiation applied to the clinical brachytherapy system and the percent depth dose and horizontal profile were measured. We compared the depth dose and horizontal profile with 4 mm diameter SRS cone for 6 MV in LINAC. We measured the PDD and horizontal profile using EBT3 film for high-precision irradiation of 1 mm diameter using Ir-192 source. In case of 4 mm diameter, the beam was measured using edge detector. In addition, all measurements were compared with the results of planning tool simulation. RESULTS In case of focal irradiation tool, the maximum dose showed at the surface for both measurement and simulation, and 26% and 32% doses at 1 mm depth, respectively. In addition, FWHM at a 1 mm depth showed that high-precision irradiation was possible with measurement and simulation results of 1.86 and 1.28 mm. In case of LINAC, the maximum dose was showed at a depth of 1 cm and 0.8 cm in the measurement and simulation, respectively. Even if the smallest cone is used, the FWHM at a dmax depth was 4.0 mm in both simulation and measurement. CONCLUSION We overcame the limitation for energy and field size through the focal irradiation tool for high-precision irradiation. The focal irradiation tool enables high dose delivery to the shallow depth. In addition, small FWHM reduced dose delivery to the periphery at a specific depth and enabled accurate dose delivery. These results mean that the focal irradiation tool can be useful in small animal experiments that require accurate doses near the shallow depth.
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Affiliation(s)
- J Son
- Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea, Republic of (South) Korea
| | - H Park
- Department of Radiological Convergence Engineering, Yonsei University, Seoul, Korea, Republic of (South) Korea
| | - E Yoon
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Korea, Republic of (South) Korea
| | - J I Kim
- Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea, Republic of (South) Korea
| | - C H Choi
- Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea, Republic of (South) Korea
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Park YI, Choi SH, Hong CS, Cho MS, Son J, Han MC, Kim J, Kim H, Kim DW, Kim JS. A Photograph-Based Visualization and Prediction Framework for Radiation-Induced Dermatitis. Int J Radiat Oncol Biol Phys 2023; 117:e480-e481. [PMID: 37785522 DOI: 10.1016/j.ijrobp.2023.06.1701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) This study aimed to suggest a photograph-based prediction system for acute radiation-induced dermatitis (RID), which can be applied to notify patients about the risk of the development of skin discomfort during radiotherapy. MATERIALS/METHODS The proposed system compared the spatial dose distribution with the RID region using the following methods. Skin photographs of patients were taken using an RGB-depth camera to acquire the shape information of RID. The skin surface data measured from the camera was registered with the shape of the external body contour using an iterative closest point algorithm. Spatial dose distribution of skin was extracted from the external body contour to a depth of 2 mm and projected onto the plane of the skin photograph using a transformation matrix for skin depth data. To compare the spatial distribution of skin dose with the shape of RID, the region of RID in patients' skin was delineated on photographs into three toxicity symptoms referring to the CTCAE criteria grade 1 (skin redness), grade 2 (dry desquamation), and grade 3 (moist desquamation). The degree of overlap between the shape of each RID and skin dose distribution was evaluated using the dice similarity coefficient (DSC). Threshold doses for predicting RID occurrence were estimated by skin isodose lines with the highest DSC. The developed system was validated using data from 19 patients who received volumetric modulated arc therapy for head-neck cancer at a single institution. RESULTS Threshold doses for RID grades 1, 2, and 3 were estimated using 18, 18, and 2 individual RID labels delineated on skin photographs, respectively. Isodose lines with the highest DSC for RID grades 1, 2, and 3 were calculated as 26.0 Gy, 36.5 Gy, and 54.0 Gy, respectively. A strong overlap (average DSC > 0.6) was observed between isodose skin lines and the shape of RID labels in all RID grades. CONCLUSION Assessing the spatial information of skin dose can be helpful in predicting acute RID. The region of RID shows a strong similarity with the skin dose distribution in head-neck patients. Visualization of skin dose on the patient photograph is potent to patient education for preparing the cosmetic discomfort during radiotherapy, which may lead to the improvement of the patient satisfaction in treatment.
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Affiliation(s)
- Y I Park
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - S H Choi
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - C S Hong
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - M S Cho
- Department of Radiation Oncology, Yongin Severance Hospital, Yonsei University College of Medicine, Gyeonggi-do, Korea, Republic of (South) Korea
| | - J Son
- Department of Radiation Oncology, Yongin Severance Hospital, Yonsei University College of Medicine, Gyeonggi-do, Korea, Republic of (South) Korea
| | - M C Han
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - J Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - H Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - D W Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
| | - J S Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea; Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea, Republic of (South) Korea
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Son J, Shin JY, Kong ST, Park J, Kwon G, Kim HD, Park KH, Jung KH, Park SJ. An interpretable and interactive deep learning algorithm for a clinically applicable retinal fundus diagnosis system by modelling finding-disease relationship. Sci Rep 2023; 13:5934. [PMID: 37045856 PMCID: PMC10097752 DOI: 10.1038/s41598-023-32518-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/28/2023] [Indexed: 04/14/2023] Open
Abstract
The identification of abnormal findings manifested in retinal fundus images and diagnosis of ophthalmic diseases are essential to the management of potentially vision-threatening eye conditions. Recently, deep learning-based computer-aided diagnosis systems (CADs) have demonstrated their potential to reduce reading time and discrepancy amongst readers. However, the obscure reasoning of deep neural networks (DNNs) has been the leading cause to reluctance in its clinical use as CAD systems. Here, we present a novel architectural and algorithmic design of DNNs to comprehensively identify 15 abnormal retinal findings and diagnose 8 major ophthalmic diseases from macula-centered fundus images with the accuracy comparable to experts. We then define a notion of counterfactual attribution ratio (CAR) which luminates the system's diagnostic reasoning, representing how each abnormal finding contributed to its diagnostic prediction. By using CAR, we show that both quantitative and qualitative interpretation and interactive adjustment of the CAD result can be achieved. A comparison of the model's CAR with experts' finding-disease diagnosis correlation confirms that the proposed model identifies the relationship between findings and diseases similarly as ophthalmologists do.
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Affiliation(s)
| | - Joo Young Shin
- Department of Ophthalmology, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | | | | | | | - Hoon Dong Kim
- Department of Ophthalmology, College of Medicine, Soonchunhyang University, Cheonan, Republic of Korea
| | - Kyu Hyung Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, Republic of Korea
| | - Kyu-Hwan Jung
- Department of Medical Device Research and Management, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, Republic of Korea.
| | - Sang Jun Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, 13620, Republic of Korea.
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Park YI, Choi SH, Hong CS, Cho MS, Son J, Han MC, Kim J, Kim H, Kim DW, Kim JS. A New Approach to Quantify and Grade Radiation Dermatitis Using Deep-Learning Segmentation in Skin Photographs. Clin Oncol (R Coll Radiol) 2023; 35:e10-e19. [PMID: 35918275 DOI: 10.1016/j.clon.2022.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 06/15/2022] [Accepted: 07/06/2022] [Indexed: 01/04/2023]
Abstract
AIMS Objective evaluation of radiation dermatitis is important for analysing the correlation between the severity of radiation dermatitis and dose distribution in clinical practice and for reliable reporting in clinical trials. We developed a novel radiation dermatitis segmentation system based on convolutional neural networks (CNNs) to consistently evaluate radiation dermatitis. MATERIALS AND METHODS The radiation dermatitis segmentation system is designed to segment the radiation dermatitis occurrence area using skin photographs and skin-dose distribution. A CNN architecture with a dilated convolution layer and skip connection was designed to estimate the radiation dermatitis area. Seventy-three skin photographs obtained from patients undergoing radiotherapy were collected for training and testing. The ground truth of radiation dermatitis segmentation is manually delineated from the skin photograph by an experienced radiation oncologist and medical physicist. We converted the skin photographs to RGB (red-green-blue) and CIELAB (lightness (L∗), red-green (a∗) and blue-yellow (b∗)) colour information and trained the network to segment faint and severe radiation dermatitis using three different input combinations: RGB, RGB + CIELAB (RGBLAB) and RGB + CIELAB + skin-dose distribution (RGBLAB_D). The proposed system was evaluated using the Dice similarity coefficient (DSC), sensitivity, specificity and normalised Matthews correlation coefficient (nMCC). A paired t-test was used to compare the results of different segmentation performances. RESULTS Optimal data composition was observed in the network trained for radiation dermatitis segmentation using skin photographs and skin-dose distribution. The average DSC, sensitivity, specificity and nMCC values of RGBLAB_D were 0.62, 0.61, 0.91 and 0.77, respectively, in faint radiation dermatitis, and 0.69, 0.78, 0.96 and 0.83, respectively, in severe radiation dermatitis. CONCLUSION Our study showed that CNN-based radiation dermatitis segmentation in skin photographs of patients undergoing radiotherapy can describe radiation dermatitis severity and pattern. Our study could aid in objectifying the radiation dermatitis grading and analysing the reliable correlation between dosimetric factors and the morphology of radiation dermatitis.
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Affiliation(s)
- Y I Park
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea; Medical Physics and Biomedical Engineering Lab (MPBEL), Yonsei University College of Medicine, Seoul, South Korea
| | - S H Choi
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea; Department of Radiation Oncology, Yongin Severance Hospital, Yongin, South Korea
| | - C-S Hong
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea.
| | - M-S Cho
- Department of Radiation Oncology, Yongin Severance Hospital, Yongin, South Korea
| | - J Son
- Department of Radiation Oncology, Yongin Severance Hospital, Yongin, South Korea
| | - M C Han
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - J Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - H Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - D W Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea
| | - J S Kim
- Department of Radiation Oncology, Yonsei University College of Medicine, Seoul, South Korea; Medical Physics and Biomedical Engineering Lab (MPBEL), Yonsei University College of Medicine, Seoul, South Korea.
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Jung S, Kim B, Lee S, Chang W, Park J, Choi C, Son J, Lee J, Wu H, Kim J, Kim J. Geometric and Dosimetric Evaluation of Using a Novel Tongue Positioning Device to Reduce Tongue Motions during Radiation Therapy for Head and Neck Cancer. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Fang H, Li F, Fu H, Sun X, Cao X, Lin F, Son J, Kim S, Quellec G, Matta S, Shankaranarayana SM, Chen YT, Wang CH, Shah NA, Lee CY, Hsu CC, Xie H, Lei B, Baid U, Innani S, Dang K, Shi W, Kamble R, Singhal N, Wang CW, Lo SC, Orlando JI, Bogunovic H, Zhang X, Xu Y. ADAM Challenge: Detecting Age-Related Macular Degeneration From Fundus Images. IEEE Trans Med Imaging 2022; 41:2828-2847. [PMID: 35507621 DOI: 10.1109/tmi.2022.3172773] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Age-related macular degeneration (AMD) is the leading cause of visual impairment among elderly in the world. Early detection of AMD is of great importance, as the vision loss caused by this disease is irreversible and permanent. Color fundus photography is the most cost-effective imaging modality to screen for retinal disorders. Cutting edge deep learning based algorithms have been recently developed for automatically detecting AMD from fundus images. However, there are still lack of a comprehensive annotated dataset and standard evaluation benchmarks. To deal with this issue, we set up the Automatic Detection challenge on Age-related Macular degeneration (ADAM), which was held as a satellite event of the ISBI 2020 conference. The ADAM challenge consisted of four tasks which cover the main aspects of detecting and characterizing AMD from fundus images, including detection of AMD, detection and segmentation of optic disc, localization of fovea, and detection and segmentation of lesions. As part of the ADAM challenge, we have released a comprehensive dataset of 1200 fundus images with AMD diagnostic labels, pixel-wise segmentation masks for both optic disc and AMD-related lesions (drusen, exudates, hemorrhages and scars, among others), as well as the coordinates corresponding to the location of the macular fovea. A uniform evaluation framework has been built to make a fair comparison of different models using this dataset. During the ADAM challenge, 610 results were submitted for online evaluation, with 11 teams finally participating in the onsite challenge. This paper introduces the challenge, the dataset and the evaluation methods, as well as summarizes the participating methods and analyzes their results for each task. In particular, we observed that the ensembling strategy and the incorporation of clinical domain knowledge were the key to improve the performance of the deep learning models.
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Kim T, Lim D, Son J, Cho K, Kim S. Reconfiguration of operation modes in silicon nanowire field-effect transistors by electrostatic virtual doping. Nanotechnology 2022; 33:415203. [PMID: 35777260 DOI: 10.1088/1361-6528/ac7dae] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 07/01/2022] [Indexed: 06/15/2023]
Abstract
In this study, we perform reconfigurable n- and p-channel operations of a tri-top-gate field-effect transistor (FET) made of a p+-i-n+silicon nanowire (SiNW). In the reconfigurable FET (RFET), two polarity gates and one control gate induce virtual electrostatic doping in the SiNW channel. The polarity gates are electrically connected to each other and program the channel type, while the control gate modulates the flow of charge carriers in the SiNW channel. The SiNW RFET features simple device design, symmetrical electrical characteristics in the n- and p-channel operation modes using p+-i-n+diode characteristics, and both operation modes exhibit high ON/OFF ratios (∼106) and high ON currents (∼1μAμm-1). The proposed device is demonstrated experimentally using a fully CMOS-compatible top-down processes.
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Affiliation(s)
- Taekham Kim
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Doohyeok Lim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Sangsig Kim
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
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13
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Antonelli M, Reinke A, Bakas S, Farahani K, Kopp-Schneider A, Landman BA, Litjens G, Menze B, Ronneberger O, Summers RM, van Ginneken B, Bilello M, Bilic P, Christ PF, Do RKG, Gollub MJ, Heckers SH, Huisman H, Jarnagin WR, McHugo MK, Napel S, Pernicka JSG, Rhode K, Tobon-Gomez C, Vorontsov E, Meakin JA, Ourselin S, Wiesenfarth M, Arbeláez P, Bae B, Chen S, Daza L, Feng J, He B, Isensee F, Ji Y, Jia F, Kim I, Maier-Hein K, Merhof D, Pai A, Park B, Perslev M, Rezaiifar R, Rippel O, Sarasua I, Shen W, Son J, Wachinger C, Wang L, Wang Y, Xia Y, Xu D, Xu Z, Zheng Y, Simpson AL, Maier-Hein L, Cardoso MJ. The Medical Segmentation Decathlon. Nat Commun 2022; 13:4128. [PMID: 35840566 PMCID: PMC9287542 DOI: 10.1038/s41467-022-30695-9] [Citation(s) in RCA: 115] [Impact Index Per Article: 57.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 05/13/2022] [Indexed: 02/05/2023] Open
Abstract
International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have been organized to focus only on specific clinical tasks. We organized the Medical Segmentation Decathlon (MSD)-a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities to investigate the hypothesis that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. MSD results confirmed this hypothesis, moreover, MSD winner continued generalizing well to a wide range of other clinical problems for the next two years. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to scientists that are not versed in AI model training.
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Affiliation(s)
- Michela Antonelli
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
| | - Annika Reinke
- Div. Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany.,HI Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Mathematics and Computer Science, University of Heidelberg, Heidelberg, Germany
| | - Spyridon Bakas
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Keyvan Farahani
- Center for Biomedical Informatics and Information Technology, National Cancer Institute (NIH), Bethesda, MD, USA
| | | | - Bennett A Landman
- Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Geert Litjens
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Bjoern Menze
- Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | | | - Ronald M Summers
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center (NIH), Bethesda, MD, USA
| | - Bram van Ginneken
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Michel Bilello
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick Bilic
- Department of Informatics, Technische Universität München, München, Germany
| | - Patrick F Christ
- Department of Informatics, Technische Universität München, München, Germany
| | - Richard K G Do
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marc J Gollub
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Stephan H Heckers
- Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Henkjan Huisman
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - William R Jarnagin
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Maureen K McHugo
- Department of Psychiatry & Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sandy Napel
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Kawal Rhode
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Catalina Tobon-Gomez
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Eugene Vorontsov
- Department of Computer Science and Software Engineering, École Polytechnique de Montréal, Montréal, QC, Canada
| | - James A Meakin
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Manuel Wiesenfarth
- Div. Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | | | - Laura Daza
- Universidad de los Andes, Bogota, Colombia
| | - Jianjiang Feng
- Department of Automation, Tsinghua University, Beijing, China
| | - Baochun He
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Fabian Isensee
- HI Applied Computer Vision Lab, Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Yuanfeng Ji
- Department of Computer Science, Xiamen University, Xiamen, China
| | - Fucang Jia
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Ildoo Kim
- Kakao Brain, Seongnam-si, Republic of Korea
| | - Klaus Maier-Hein
- Cerebriu A/S, Copenhagen, Denmark.,Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Dorit Merhof
- Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
| | - Akshay Pai
- Cerebriu A/S, Copenhagen, Denmark.,Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Mathias Perslev
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Oliver Rippel
- Institute of Imaging & Computer Vision, RWTH Aachen University, Aachen, Germany
| | - Ignacio Sarasua
- Lab for Artificial Intelligence in Medical Imaging (AI-Med), Department of Child and Adolescent Psychiatry, University Hospital, LMU München, Germany
| | - Wei Shen
- MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China
| | | | - Christian Wachinger
- Lab for Artificial Intelligence in Medical Imaging (AI-Med), Department of Child and Adolescent Psychiatry, University Hospital, LMU München, Germany
| | - Liansheng Wang
- Department of Computer Science, Xiamen University, Xiamen, China
| | - Yan Wang
- Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China
| | - Yingda Xia
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Zhanwei Xu
- Department of Automation, Tsinghua University, Beijing, China
| | | | - Amber L Simpson
- School of Computing/Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Lena Maier-Hein
- Div. Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany.,HI Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Mathematics and Computer Science, University of Heidelberg, Heidelberg, Germany.,Medical Faculty, University of Heidelberg, Heidelberg, Germany
| | - M Jorge Cardoso
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
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14
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Kim MG, Ryu J, Son J, Han J. Virtual object sizes for efficient and convenient mid-air manipulation. Vis Comput 2022; 38:3463-3474. [PMID: 35791413 PMCID: PMC9247950 DOI: 10.1007/s00371-022-02555-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/21/2022] [Indexed: 06/15/2023]
Abstract
UNLABELLED It has been taken for granted that the sizes of virtual objects affect the efficiency and convenience of mid-air manipulation in immersive virtual environments. If a virtual object is too small or too large, for example, manipulating it becomes a difficult task. Nevertheless, the virtual object sizes that are optimal and convenient have rarely been studied. In this paper, we select a virtual object with many distinct geometric features and conduct user studies via docking tasks. Through the user studies, the optimal and convenient sizes for mid-air manipulation are estimated. In order to verify the results, a proxy-based manipulation method is designed and implemented, where the proxy is created with the estimated optimal size. The test based on the method shows that the optimal-size proxy enables users to manipulate efficiently virtual objects and the estimated range of convenient sizes is also preferred by the users. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s00371-022-02555-6.
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Affiliation(s)
- Myoung Gon Kim
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | - JiSeok Ryu
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | - Jaemin Son
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | - JungHyun Han
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
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15
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Liu R, Wang X, Wu Q, Dai L, Fang X, Yan T, Son J, Tang S, Li J, Gao Z, Galdran A, Poorneshwaran JM, Liu H, Wang J, Chen Y, Porwal P, Wei Tan GS, Yang X, Dai C, Song H, Chen M, Li H, Jia W, Shen D, Sheng B, Zhang P. DeepDRiD: Diabetic Retinopathy-Grading and Image Quality Estimation Challenge. Patterns (N Y) 2022; 3:100512. [PMID: 35755875 PMCID: PMC9214346 DOI: 10.1016/j.patter.2022.100512] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 03/28/2022] [Accepted: 04/25/2022] [Indexed: 12/19/2022]
Abstract
We described a challenge named "Diabetic Retinopathy (DR)-Grading and Image Quality Estimation Challenge" in conjunction with ISBI 2020 to hold three sub-challenges and develop deep learning models for DR image assessment and grading. The scientific community responded positively to the challenge, with 34 submissions from 574 registrations. In the challenge, we provided the DeepDRiD dataset containing 2,000 regular DR images (500 patients) and 256 ultra-widefield images (128 patients), both having DR quality and grading annotations. We discussed details of the top 3 algorithms in each sub-challenges. The weighted kappa for DR grading ranged from 0.93 to 0.82, and the accuracy for image quality evaluation ranged from 0.70 to 0.65. The results showed that image quality assessment can be used as a further target for exploration. We also have released the DeepDRiD dataset on GitHub to help develop automatic systems and improve human judgment in DR screening and diagnosis.
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Affiliation(s)
- Ruhan Liu
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.,MoE Key Lab of Artificial Intelligence, Artificial Intelligence Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Xiangning Wang
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Qiang Wu
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Ling Dai
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.,MoE Key Lab of Artificial Intelligence, Artificial Intelligence Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Xi Fang
- Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Tao Yan
- Department of Electromechanical Engineering, University of Macau, Macao, China
| | | | - Shiqi Tang
- Department of Mathematics, City University of Hong Kong, Hong Kong, China
| | - Jiang Li
- Institute of Image Processing and Pattern Recognition, Department of Automation, Shanghai Jiao Tong University, Shanghai, China
| | - Zijian Gao
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China
| | | | | | - Hao Liu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China
| | - Jie Wang
- School of Computer Science and Engineering, Beihang University, Beijing, China
| | - Yerui Chen
- Nanjing University of Science and Technology, Nanjing, China
| | - Prasanna Porwal
- Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India
| | - Gavin Siew Wei Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Xiaokang Yang
- MoE Key Lab of Artificial Intelligence, Artificial Intelligence Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Chao Dai
- Shanghai Zhi Tang Health Technology Co., LTD., China
| | - Haitao Song
- MoE Key Lab of Artificial Intelligence, Artificial Intelligence Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Mingang Chen
- Shanghai Key Laboratory of Computer Software Testing & Evaluating, Shanghai Development Center of Computer Software Technology, Shanghai, China
| | - Huating Li
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.,Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.,Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Dinggang Shen
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.,Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Bin Sheng
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.,MoE Key Lab of Artificial Intelligence, Artificial Intelligence Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Ping Zhang
- Department of Computer Science and Engineering, The Ohio State University, Ohio, USA.,Department of Biomedical Informatics, The Ohio State University, Ohio, USA.,Translational Data Analytics Institute, The Ohio State University, Ohio, USA
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16
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Park JE, Son J, Seo Y, Han JS. HM-Chromanone Ameliorates Hyperglycemia and Dyslipidemia in Type 2 Diabetic Mice. Nutrients 2022; 14:nu14091951. [PMID: 35565920 PMCID: PMC9101766 DOI: 10.3390/nu14091951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/26/2022] [Accepted: 05/05/2022] [Indexed: 02/04/2023] Open
Abstract
The effects of (E)-5-hydroxy-7-methoxy-3-(2-hydroxybenzyl)-4-chromanone (HMC) on hyperglycemia and dyslipidemia were investigated in diabetic mice. Mice were separated into three groups: db/db, rosiglitazone and HMC. Blood glucose or glycosylated hemoglobin values in HMC-treated mice were significantly lower compared to db/db mice. Total cholesterol, LDL-cholesterol, and triglyceride values were lower, and HDL-C levels were higher, in the HMC group compared to the diabetic and rosiglitazone groups. HMC markedly increased IRS-1Tyr612, AktSer473 and PI3K levels and plasma membrane GLUT4 levels in skeletal muscle, suggesting improved insulin resistance. HMC also significantly stimulated AMPKThr172 and PPARα in the liver, and ameliorated dyslipidemia by inhibiting SREBP-1c and FAS. Consequently, HMC reduced hyperglycemia by improving the expression of insulin-resistance-related genes and improved dyslipidemia by regulating fatty acid synthase and oxidation-related genes in db/db mice. Therefore, HMC could ameliorate hyperglycemia and dyslipidemia in type 2 diabetic mice.
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Affiliation(s)
- Jae Eun Park
- Department of Food Science and Nutrition, Pusan National University, Busan 46241, Korea;
| | - Jaemin Son
- Division of Marine Bioscience, Ocean Science & Technology School, Korea Maritime and Ocean University, Busan 49112, Korea; (J.S.); (Y.S.)
| | - Youngwan Seo
- Division of Marine Bioscience, Ocean Science & Technology School, Korea Maritime and Ocean University, Busan 49112, Korea; (J.S.); (Y.S.)
| | - Ji Sook Han
- Department of Food Science and Nutrition, Pusan National University, Busan 46241, Korea;
- Correspondence: ; Tel.: +82-51-510-2836; Fax: +82-51-583-3648
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17
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Yang Y, Jeon J, Son J, Cho K, Kim S. NAND and NOR logic-in-memory comprising silicon nanowire feedback field-effect transistors. Sci Rep 2022; 12:3643. [PMID: 35256631 PMCID: PMC8901646 DOI: 10.1038/s41598-022-07368-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/15/2022] [Indexed: 11/10/2022] Open
Abstract
The processing of large amounts of data requires a high energy efficiency and fast processing time for high-performance computing systems. However, conventional von Neumann computing systems have performance limitations because of bottlenecks in data movement between separated processing and memory hierarchy, which causes latency and high power consumption. To overcome this hindrance, logic-in-memory (LIM) has been proposed that performs both data processing and memory operations. Here, we present a NAND and NOR LIM composed of silicon nanowire feedback field-effect transistors, whose configuration resembles that of CMOS logic gate circuits. The LIM can perform memory operations to retain its output logic under zero-bias conditions as well as logic operations with a high processing speed of nanoseconds. The newly proposed dynamic voltage-transfer characteristics verify the operating principle of the LIM. This study demonstrates that the NAND and NOR LIM has promising potential to resolve power and processing speed issues.
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Affiliation(s)
- Yejin Yang
- Department of Semiconductor Systems Engineering, Korea University, Seoul, Republic of Korea
| | - Juhee Jeon
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Sangsig Kim
- Department of Semiconductor Systems Engineering, Korea University, Seoul, Republic of Korea. .,Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.
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18
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Kang B, Lee J, Xue L, Son J, Wu H, Kim H, Kang H. Prediction of Delayed Lymphopenia at the Time of Consolidation Immunotherapy After Chemoradiotherapy in Locally Advanced Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.1248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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19
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Choi S, Son J, Cho K, Kim S. One-transistor static random-access memory cell array comprising single-gated feedback field-effect transistors. Sci Rep 2021; 11:17983. [PMID: 34504236 PMCID: PMC8429708 DOI: 10.1038/s41598-021-97479-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 08/19/2021] [Indexed: 11/09/2022] Open
Abstract
In this study, we fabricated a 2 × 2 one-transistor static random-access memory (1T-SRAM) cell array comprising single-gated feedback field-effect transistors and examined their operation and memory characteristics. The individual 1T-SRAM cell had a retention time of over 900 s, nondestructive reading characteristics of 10,000 s, and an endurance of 108 cycles. The standby power of the individual 1T-SRAM cell was estimated to be 0.7 pW for holding the "0" state and 6 nW for holding the "1" state. For a selected cell in the 2 × 2 1T-SRAM cell array, nondestructive reading of the memory was conducted without any disturbance in the half-selected cells. This immunity to disturbances validated the reliability of the 1T-SRAM cell array.
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Affiliation(s)
- Sangik Choi
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea
| | - Sangsig Kim
- Department of Semiconductor Systems Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea. .,Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea.
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20
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Jeon J, Park YS, Woo S, Lim D, Son J, Kim S. Effect of Ge Mole Fraction on Performance of Underlapped Gate-All-Around SiGe-Source Tunneling Field-Effect Transistors. J Nanosci Nanotechnol 2021; 21:4310-4314. [PMID: 33714319 DOI: 10.1166/jnn.2021.19401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
In this paper, we propose the design optimization of underlapped Si1-xGex-source tunneling field-effect transistors (TFETs) with a gate-all-around structure. The band-to-band tunneling rates, tunneling barrier widths, I-V transfer characteristics, threshold voltages, on/off current ratios, and subthreshold swings (SSs) were analyzed by varying the Ge mole fraction of the Si1-xGex source using a commercial device simulator. In particular, a Si0.2Ge0.8-source TFET among our proposed TFETs exhibits an on/off current ratio of approximately 1013, and SS of 27.4 mV/dec.
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Affiliation(s)
- Juhee Jeon
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Young-Soo Park
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Sola Woo
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Doohyeok Lim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Sangsig Kim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
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21
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Son J, Lim D, Kim S. Steep Switching Characteristics of Partially Gated p+- n+- i- n+ Silicon-Nanowire Transistors. J Nanosci Nanotechnol 2021; 21:4330-4335. [PMID: 33714323 DOI: 10.1166/jnn.2021.19398] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
In this study, we examine the electrical characteristics of p+-n+-i-n+ silicon-nanowire field-effect transistors with partially gated channels. The silicon-nanowire field-effect transistors operate with barrier height modulation through positive feedback loops of charge carriers triggered by impact ionization. Our field-effect transistors exhibit outstanding switching characteristics, with an on current of ˜10-4 A, an on/off current ratio of ˜106, and a point subthreshold swing of ˜23 mV/dec. Moreover, the devices inhibit ambipolar characteristics because of the use of the partially gated structure and feature the p-channel operation mode.
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Affiliation(s)
- Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Doohyeok Lim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Sangsig Kim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
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22
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Park YS, Lim D, Son J, Jeon J, Cho K, Kim S. Inverting logic-in-memory cells comprising silicon nanowire feedback field-effect transistors. Nanotechnology 2021; 32:225202. [PMID: 33618339 DOI: 10.1088/1361-6528/abe894] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 02/19/2021] [Indexed: 06/12/2023]
Abstract
In this paper, we propose inverting logic-in-memory (LIM) cells comprising silicon nanowire feedback field-effect transistors with steep switching and holding characteristics. The timing diagrams of the proposed inverting LIM cells under dynamic and static conditions are investigated via mixed-mode technology computer-aided design simulation to verify the performance. The inverting LIM cells have an operating speed of the order of nanoseconds, an ultra-high voltage gain, and a longer retention time than that of conventional dynamic random access memory. The disturbance characteristics of half-selected cells within an inverting LIM array confirm the appropriate functioning of the random access memory array.
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Affiliation(s)
- Young-Soo Park
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Doohyeok Lim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Jaemin Son
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Juhee Jeon
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Kyoungah Cho
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Sangsig Kim
- Department of Electrical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
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23
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Son J, Shin JY, Chun EJ, Jung KH, Park KH, Park SJ. Predicting High Coronary Artery Calcium Score From Retinal Fundus Images With Deep Learning Algorithms. Transl Vis Sci Technol 2020; 9:28. [PMID: 33184590 PMCID: PMC7410115 DOI: 10.1167/tvst.9.2.28] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 03/06/2020] [Indexed: 01/04/2023] Open
Abstract
Purpose To evaluate high accumulation of coronary artery calcium (CAC) from retinal fundus images with deep learning technologies as an inexpensive and radiation-free screening method. Methods Individuals who underwent bilateral retinal fundus imaging and CAC score (CACS) evaluation from coronary computed tomography scans on the same day were identified. With this database, performances of deep learning algorithms (inception-v3) to distinguish high CACS from CACS of 0 were evaluated at various thresholds for high CACS. Vessel-inpainted and fovea-inpainted images were also used as input to investigate areas of interest in determining CACS. Results A total of 44,184 images from 20,130 individuals were included. A deep learning algorithm for discrimination of no CAC from CACS >100 achieved area under receiver operating curve (AUROC) of 82.3% (79.5%–85.0%) and 83.2% (80.2%–86.3%) using unilateral and bilateral fundus images, respectively, under a 5-fold cross validation setting. AUROC increased as the criterion for high CACS was increased, showing a plateau at 100 and losing significant improvement thereafter. AUROC decreased when fovea was inpainted and decreased further when vessels were inpainted, whereas AUROC increased when bilateral images were used as input. Conclusions Visual patterns of retinal fundus images in subjects with CACS > 100 could be recognized by deep learning algorithms compared with those with no CAC. Exploiting bilateral images improves discrimination performance, and ablation studies removing retinal vasculature or fovea suggest that recognizable patterns reside mainly in these areas. Translational Relevance Retinal fundus images can be used by deep learning algorithms for prediction of high CACS.
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Affiliation(s)
| | - Joo Young Shin
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Korea
| | - Eun Ju Chun
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea
| | | | - Kyu Hyung Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Sang Jun Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
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Son J, Tran T, Yao M, Michener C. Factors associated with successful same-day discharge in patients undergoing minimally invasive hysterectomy for endometrial cancer and atypical complex hyperplasia. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2020.05.547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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AlHilli M, Son J, Carr C, Yao M, Michener C, Rose P. Mismatch repair deficiency is predictive of improved response to radiation therapy in patients with advanced or recurrent endometrial cancer. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2020.05.406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Son J, Carr C, Chambers LM, Michener C, Meng Y, Yen T, Beavis A, Stone R, Wethington S, Burkett W, Richardson D, Staley AS, Ahn S, Gehrig P, Torres D, Dowdy S, Sullivan M, Modesitt S, Watson C, Secord A, Veade A, Havrilesky L, Loreen A, Griffin K, Jackson A, Fader AN, Ricci S. Adjuvant treatment in high intermediate risk early stage endometrial cancer. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2019.11.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Orlando JI, Fu H, Barbosa Breda J, van Keer K, Bathula DR, Diaz-Pinto A, Fang R, Heng PA, Kim J, Lee J, Lee J, Li X, Liu P, Lu S, Murugesan B, Naranjo V, Phaye SSR, Shankaranarayana SM, Sikka A, Son J, van den Hengel A, Wang S, Wu J, Wu Z, Xu G, Xu Y, Yin P, Li F, Zhang X, Xu Y, Bogunović H. REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs. Med Image Anal 2020; 59:101570. [DOI: 10.1016/j.media.2019.101570] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/26/2019] [Accepted: 10/01/2019] [Indexed: 01/01/2023]
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Son J, Shin JY, Kim HD, Jung KH, Park KH, Park SJ. Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images. Ophthalmology 2020; 127:85-94. [DOI: 10.1016/j.ophtha.2019.05.029] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Revised: 05/03/2019] [Accepted: 05/24/2019] [Indexed: 12/25/2022] Open
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Abstract
In this paper, we aimed to understand and analyze the outputs of a convolutional neural network model that classifies the laterality of fundus images. Our model not only automatizes the classification process, which results in reducing the labors of clinicians, but also highlights the key regions in the image and evaluates the uncertainty for the decision with proper analytic tools. Our model was trained and tested with 25,911 fundus images (43.4% of macula-centered images and 28.3% each of superior and nasal retinal fundus images). Also, activation maps were generated to mark important regions in the image for the classification. Then, uncertainties were quantified to support explanations as to why certain images were incorrectly classified under the proposed model. Our model achieved a mean training accuracy of 99%, which is comparable to the performance of clinicians. Strong activations were detected at the location of optic disc and retinal blood vessels around the disc, which matches to the regions that clinicians attend when deciding the laterality. Uncertainty analysis discovered that misclassified images tend to accompany with high prediction uncertainties and are likely ungradable. We believe that visualization of informative regions and the estimation of uncertainty, along with presentation of the prediction result, would enhance the interpretability of neural network models in a way that clinicians can be benefitted from using the automatic classification system.
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Affiliation(s)
- Yeonwoo Jang
- Department of Statistics, University of Oxford, Oxford, UK
| | - Jaemin Son
- VUNO Inc., 6F, 507, Gangnam-daero, Seocho-gu, Seoul, Republic of Korea
| | - Kyu Hyung Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Sang Jun Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Kyu-Hwan Jung
- VUNO Inc., 6F, 507, Gangnam-daero, Seocho-gu, Seoul, Republic of Korea.
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Porwal P, Pachade S, Kokare M, Deshmukh G, Son J, Bae W, Liu L, Wang J, Liu X, Gao L, Wu T, Xiao J, Wang F, Yin B, Wang Y, Danala G, He L, Choi YH, Lee YC, Jung SH, Li Z, Sui X, Wu J, Li X, Zhou T, Toth J, Baran A, Kori A, Chennamsetty SS, Safwan M, Alex V, Lyu X, Cheng L, Chu Q, Li P, Ji X, Zhang S, Shen Y, Dai L, Saha O, Sathish R, Melo T, Araújo T, Harangi B, Sheng B, Fang R, Sheet D, Hajdu A, Zheng Y, Mendonça AM, Zhang S, Campilho A, Zheng B, Shen D, Giancardo L, Quellec G, Mériaudeau F. IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge. Med Image Anal 2019; 59:101561. [PMID: 31671320 DOI: 10.1016/j.media.2019.101561] [Citation(s) in RCA: 89] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 09/09/2019] [Accepted: 09/16/2019] [Indexed: 02/07/2023]
Abstract
Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid vision loss. However, implementation of DR screening programs is challenging due to the scarcity of medical professionals able to screen a growing global diabetic population at risk for DR. Computer-aided disease diagnosis in retinal image analysis could provide a sustainable approach for such large-scale screening effort. The recent scientific advances in computing capacity and machine learning approaches provide an avenue for biomedical scientists to reach this goal. Aiming to advance the state-of-the-art in automatic DR diagnosis, a grand challenge on "Diabetic Retinopathy - Segmentation and Grading" was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI - 2018). In this paper, we report the set-up and results of this challenge that is primarily based on Indian Diabetic Retinopathy Image Dataset (IDRiD). There were three principal sub-challenges: lesion segmentation, disease severity grading, and localization of retinal landmarks and segmentation. These multiple tasks in this challenge allow to test the generalizability of algorithms, and this is what makes it different from existing ones. It received a positive response from the scientific community with 148 submissions from 495 registrations effectively entered in this challenge. This paper outlines the challenge, its organization, the dataset used, evaluation methods and results of top-performing participating solutions. The top-performing approaches utilized a blend of clinical information, data augmentation, and an ensemble of models. These findings have the potential to enable new developments in retinal image analysis and image-based DR screening in particular.
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Affiliation(s)
- Prasanna Porwal
- Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India; School of Biomedical Informatics, University of Texas Health Science Center at Houston, USA.
| | - Samiksha Pachade
- Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India; School of Biomedical Informatics, University of Texas Health Science Center at Houston, USA
| | - Manesh Kokare
- Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India
| | | | | | | | - Lihong Liu
- Ping An Technology (Shenzhen) Co.,Ltd, China
| | | | - Xinhui Liu
- Ping An Technology (Shenzhen) Co.,Ltd, China
| | | | - TianBo Wu
- Ping An Technology (Shenzhen) Co.,Ltd, China
| | - Jing Xiao
- Ping An Technology (Shenzhen) Co.,Ltd, China
| | | | | | - Yunzhi Wang
- School of Electrical and Computer Engineering, University of Oklahoma, USA
| | - Gopichandh Danala
- School of Electrical and Computer Engineering, University of Oklahoma, USA
| | - Linsheng He
- School of Electrical and Computer Engineering, University of Oklahoma, USA
| | - Yoon Ho Choi
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Yeong Chan Lee
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Sang-Hyuk Jung
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea
| | - Zhongyu Li
- Department of Computer Science, University of North Carolina at Charlotte, USA
| | - Xiaodan Sui
- School of Information Science and Engineering, Shandong Normal University, China
| | - Junyan Wu
- Cleerly Inc., New York, United States
| | | | - Ting Zhou
- University at Buffalo, New York, United States
| | - Janos Toth
- University of Debrecen, Faculty of Informatics 4002 Debrecen, POB 400, Hungary
| | - Agnes Baran
- University of Debrecen, Faculty of Informatics 4002 Debrecen, POB 400, Hungary
| | | | | | | | | | - Xingzheng Lyu
- College of Computer Science and Technology, Zhejiang University, Hangzhou, China; Machine Learning for Bioimage Analysis Group, Bioinformatics Institute, A*STAR, Singapore
| | - Li Cheng
- Machine Learning for Bioimage Analysis Group, Bioinformatics Institute, A*STAR, Singapore; Department of Electric and Computer Engineering, University of Alberta, Canada
| | - Qinhao Chu
- School of Computing, National University of Singapore, Singapore
| | - Pengcheng Li
- School of Computing, National University of Singapore, Singapore
| | - Xin Ji
- Beijing Shanggong Medical Technology Co., Ltd., China
| | - Sanyuan Zhang
- College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Yaxin Shen
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, China; MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China
| | - Ling Dai
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, China; MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China
| | | | | | - Tânia Melo
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
| | - Teresa Araújo
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal; FEUP - Faculty of Engineering of the University of Porto, Porto, Portugal
| | - Balazs Harangi
- University of Debrecen, Faculty of Informatics 4002 Debrecen, POB 400, Hungary
| | - Bin Sheng
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, China; MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China
| | - Ruogu Fang
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, USA
| | | | - Andras Hajdu
- University of Debrecen, Faculty of Informatics 4002 Debrecen, POB 400, Hungary
| | - Yuanjie Zheng
- School of Information Science and Engineering, Shandong Normal University, China
| | - Ana Maria Mendonça
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal; FEUP - Faculty of Engineering of the University of Porto, Porto, Portugal
| | - Shaoting Zhang
- Department of Computer Science, University of North Carolina at Charlotte, USA
| | - Aurélio Campilho
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal; FEUP - Faculty of Engineering of the University of Porto, Porto, Portugal
| | - Bin Zheng
- School of Electrical and Computer Engineering, University of Oklahoma, USA
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA; Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Luca Giancardo
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, USA
| | | | - Fabrice Mériaudeau
- Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Malaysia; ImViA/IFTIM, Université de Bourgogne, Dijon, France
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Chen X, Grimm J, Baker B, Son J, Siu C, Redmond K, Bettegowda C, Lim M, Kleinberg L. Fractionated Stereotactic Radiosurgery for Brainstem Metastasis and Brainstem Tolerance. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.2328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Son J, Carr C, Radeva M, Priyadarshini A, Marquard J, AlHilli M. Molecular and pathologic features of endometrial cancer in young patients. Gynecol Oncol 2019. [DOI: 10.1016/j.ygyno.2019.03.211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Son J, Carr C, Yao M, Radeva M, Priyadarshini A, Marquard J, AlHilli M. Characterization of endometrial cancer in young patients diagnosed under the age of 40 years. Gynecol Oncol 2019. [DOI: 10.1016/j.ygyno.2019.04.615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Son J, Park SJ, Jung KH. Towards Accurate Segmentation of Retinal Vessels and the Optic Disc in Fundoscopic Images with Generative Adversarial Networks. J Digit Imaging 2019; 32:499-512. [PMID: 30291477 PMCID: PMC6499859 DOI: 10.1007/s10278-018-0126-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
Abstract
Automatic segmentation of the retinal vasculature and the optic disc is a crucial task for accurate geometric analysis and reliable automated diagnosis. In recent years, Convolutional Neural Networks (CNN) have shown outstanding performance compared to the conventional approaches in the segmentation tasks. In this paper, we experimentally measure the performance gain for Generative Adversarial Networks (GAN) framework when applied to the segmentation tasks. We show that GAN achieves statistically significant improvement in area under the receiver operating characteristic (AU-ROC) and area under the precision and recall curve (AU-PR) on two public datasets (DRIVE, STARE) by segmenting fine vessels. Also, we found a model that surpassed the current state-of-the-art method by 0.2 - 1.0% in AU-ROC and 0.8 - 1.2% in AU-PR and 0.5 - 0.7% in dice coefficient. In contrast, significant improvements were not observed in the optic disc segmentation task on DRIONS-DB, RIM-ONE (r3) and Drishti-GS datasets in AU-ROC and AU-PR.
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Affiliation(s)
- Jaemin Son
- VUNO Inc., 6F, 507, Gangnam-daero, Seocho-gu, Seoul, Republic of Korea
| | - Sang Jun Park
- Department of Ophthalmology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Kyu-Hwan Jung
- VUNO Inc., 6F, 507, Gangnam-daero, Seocho-gu, Seoul, Republic of Korea
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Yen T, Beavis A, Stone R, Wethington S, Carr C, Son J, Chambers LM, Ricci S, Burkett W, Richardson D, Staley A, Ahn S, Gehrig P, Torres D, Dowdy S, Sullivan M, Modesitt S, Watson C, Secord A, Veade A, Havrilesky L, Loreen A, Griffin K, Jackson A, Fader A. Early-stage endometrial cancer with lymphovascular space invasion: Chemotherapy improves progression free survival and reduces distant metastases. Gynecol Oncol 2019. [DOI: 10.1016/j.ygyno.2019.04.675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Cho S, Son J, Kim H, Jeong J, Lee S, Lim Y, Lee S, Yoon M, Shin D. The Development of New Dosimetry System using an Optic-Disk Radiation Sensor for Pencil Beam Scanning Mode. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.07.1379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Peng L, Chen L, Han P, Baker B, Shen C, Gui C, Sheikh K, Ames H, Kirschbaum T, Silvestri F, Son J, Robinson A, Huang E, Grimm J, Redmond K, Lim M, Lee J, Kleinberg L. Concurrent Immunotherapy Usage and Asymmetric Growth May Distinguish True Progression from Treatment Effect in Growing Brain Metastases after Stereotactic Radiosurgery. Int J Radiat Oncol Biol Phys 2018. [DOI: 10.1016/j.ijrobp.2018.07.919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Park SJ, Shin JY, Kim S, Son J, Jung KH, Park KH. A Novel Fundus Image Reading Tool for Efficient Generation of a Multi-dimensional Categorical Image Database for Machine Learning Algorithm Training. J Korean Med Sci 2018; 33:e239. [PMID: 30344460 PMCID: PMC6193885 DOI: 10.3346/jkms.2018.33.e239] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 07/10/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system. METHODS A 5-step retinal fundus image reading tool was developed that rates image quality, presence of abnormality, findings with location information, diagnoses, and clinical significance. Each image was evaluated by 3 different graders. Agreements among graders for each decision were evaluated. RESULTS The 234,242 readings of 79,458 images were collected from 55 licensed ophthalmologists during 6 months. The 34,364 images were graded as abnormal by at-least one rater. Of these, all three raters agreed in 46.6% in abnormality, while 69.9% of the images were rated as abnormal by two or more raters. Agreement rate of at-least two raters on a certain finding was 26.7%-65.2%, and complete agreement rate of all-three raters was 5.7%-43.3%. As for diagnoses, agreement of at-least two raters was 35.6%-65.6%, and complete agreement rate was 11.0%-40.0%. Agreement of findings and diagnoses were higher when restricted to images with prior complete agreement on abnormality. Retinal/glaucoma specialists showed higher agreements on findings and diagnoses of their corresponding subspecialties. CONCLUSION This novel reading tool for retinal fundus images generated a large-scale dataset with high level of information, which can be utilized in future development of machine learning-based algorithms for automated identification of abnormal conditions and clinical decision supporting system. These results emphasize the importance of addressing grader variability in algorithm developments.
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Affiliation(s)
- Sang Jun Park
- Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Joo Young Shin
- Department of Ophthalmology, Dongguk University Ilsan Hospital, Goyang, Korea
| | | | | | | | - Kyu Hyung Park
- Department of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
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Gordon AC, Gillespie C, Son J, Polhill T, Leibman S, Smith GS. Long-term outcomes of laparoscopic large hiatus hernia repair with nonabsorbable mesh. Dis Esophagus 2018; 31:4850447. [PMID: 29444215 DOI: 10.1093/dote/dox156] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Accepted: 12/06/2017] [Indexed: 12/11/2022]
Abstract
The use of mesh to augment suture repair of large hiatus hernias remains controversial. Repair with mesh may help reduce the recurrence rate of primary repair, but concerns about the potential for serious complications, such as mesh erosion or stricturing, continue to limit its use. We aim to evaluate the long-term outcome of primary hiatus hernia repair with lightweight polypropylene mesh (TiMesh) specifically looking at rates of clinical recurrence, dysphagia, and mesh-related complications. From a prospectively maintained database, 50 consecutive patients who underwent elective primary laparoscopic hiatal hernia repair with TiMesh between January 2005 and December 2007 were identified. Case notes and postoperative endoscopy reports were reviewed. Clinical outcomes were evaluated using a structured questionnaire, including a validated dysphagia score. Of the 50 patients identified, 36 (72%) were contactable for follow-up. At a median follow-up of 9 years, the majority of patients (97%) regarded their surgery as successful. Twelve patients (33%) reported a recurrence of their symptoms, but only 4 (11%) reported that their symptoms were as severe as prior to the surgery. There was no significant difference between pre- and postoperative dysphagia scores. Postoperative endoscopy reports were available for 32 patients at a median time point of 4 years postoperatively, none of which revealed any mesh-related complications. One patient had undergone a revision procedure for a recurrent hernia at another institution. In this series, primary repair of large hiatus hernia with nonabsorbable mesh was not associated with any adverse effects over time. Patient satisfaction with symptomatic outcome remained high in the long term.
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Affiliation(s)
- A C Gordon
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - C Gillespie
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - J Son
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - T Polhill
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - S Leibman
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - G S Smith
- Department of Upper Gastrointestinal Surgery, Royal North Shore Hospital, Sydney, New South Wales, Australia
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Kang KT, Son J, Suh DS, Kwon SK, Kwon OR, Koh YG. Patient-specific medial unicompartmental knee arthroplasty has a greater protective effect on articular cartilage in the lateral compartment: A Finite Element Analysis. Bone Joint Res 2018; 7:20-27. [PMID: 29305427 PMCID: PMC5805830 DOI: 10.1302/2046-3758.71.bjr-2017-0115.r2] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES Patient-specific (PS) implantation surgical technology has been introduced in recent years and a gradual increase in the associated number of surgical cases has been observed. PS technology uses a patient's own geometry in designing a medical device to provide minimal bone resection with improvement in the prosthetic bone coverage. However, whether PS unicompartmental knee arthroplasty (UKA) provides a better biomechanical effect than standard off-the-shelf prostheses for UKA has not yet been determined, and still remains controversial in both biomechanical and clinical fields. Therefore, the aim of this study was to compare the biomechanical effect between PS and standard off-the-shelf prostheses for UKA. METHODS The contact stresses on the polyethylene (PE) insert, articular cartilage and lateral meniscus were evaluated in PS and standard off-the-shelf prostheses for UKA using a validated finite element model. Gait cycle loading was applied to evaluate the biomechanical effect in the PS and standard UKAs. RESULTS The contact stresses on the PE insert were similar for both the PS and standard UKAs. Compared with the standard UKA, the PS UKA did not show any biomechanical effect on the medial PE insert. However, the contact stresses on the articular cartilage and the meniscus in the lateral compartment following the PS UKA exhibited closer values to the healthy knee joint compared with the standard UKA. CONCLUSION The PS UKA provided mechanics closer to those of the normal knee joint. The decreased contact stress on the opposite compartment may reduce the overall risk of progressive osteoarthritis.Cite this article: K-T. Kang, J. Son, D-S. Suh, S. K. Kwon, O-R. Kwon, Y-G. Koh. Patient-specific medial unicompartmental knee arthroplasty has a greater protective effect on articular cartilage in the lateral compartment: A Finite Element Analysis. Bone Joint Res 2018;7:20-27. DOI: 10.1302/2046-3758.71.BJR-2017-0115.R2.
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Affiliation(s)
- K-T. Kang
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea
| | - J. Son
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea
| | - D-S. Suh
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - S. K. Kwon
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - O-R. Kwon
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - Y-G. Koh
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
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Kang KT, Koh YG, Son J, Kwon OR, Lee JS, Kwon SK. A computational simulation study to determine the biomechanical influence of posterior condylar offset and tibial slope in cruciate retaining total knee arthroplasty. Bone Joint Res 2018; 7:69-78. [PMID: 29330345 PMCID: PMC5805829 DOI: 10.1302/2046-3758.71.bjr-2017-0143.r1] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Objectives Posterior condylar offset (PCO) and posterior tibial slope (PTS) are critical factors in total knee arthroplasty (TKA). A computational simulation was performed to evaluate the biomechanical effect of PCO and PTS on cruciate retaining TKA. Methods We generated a subject-specific computational model followed by the development of ± 1 mm, ± 2 mm and ± 3 mm PCO models in the posterior direction, and -3°, 0°, 3° and 6° PTS models with each of the PCO models. Using a validated finite element (FE) model, we investigated the influence of the changes in PCO and PTS on the contact stress in the patellar button and the forces on the posterior cruciate ligament (PCL), patellar tendon and quadriceps muscles under the deep knee-bend loading conditions. Results Contact stress on the patellar button increased and decreased as PCO translated to the anterior and posterior directions, respectively. In addition, contact stress on the patellar button decreased as PTS increased. These trends were consistent in the FE models with altered PCO. Higher quadriceps muscle and patellar tendon force are required as PCO translated in the anterior direction with an equivalent flexion angle. However, as PTS increased, quadriceps muscle and patellar tendon force reduced in each PCO condition. The forces exerted on the PCL increased as PCO translated to the posterior direction and decreased as PTS increased. Conclusion The change in PCO alternatively provided positive and negative biomechanical effects, but it led to a reduction in a negative biomechanical effect as PTS increased. Cite this article: K-T. Kang, Y-G. Koh, J. Son, O-R. Kwon, J-S. Lee, S. K. Kwon. A computational simulation study to determine the biomechanical influence of posterior condylar offset and tibial slope in cruciate retaining total knee arthroplasty. Bone Joint Res 2018;7:69–78. DOI: 10.1302/2046-3758.71.BJR-2017-0143.R1.
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Affiliation(s)
- K-T Kang
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea
| | - Y-G Koh
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - J Son
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea
| | - O-R Kwon
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - J-S Lee
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - S K Kwon
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
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Sandilands LJ, Kyung W, Kim SY, Son J, Kwon J, Kang TD, Yoshida Y, Moon SJ, Kim C, Noh TW. Spin-Orbit Coupling and Interband Transitions in the Optical Conductivity of Sr_{2}RhO_{4}. Phys Rev Lett 2017; 119:267402. [PMID: 29328701 DOI: 10.1103/physrevlett.119.267402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2017] [Indexed: 06/07/2023]
Abstract
The prototypical correlated metal Sr_{2}RhO_{4} was studied using optical and photoemission spectroscopy. At low energies and temperatures, the optical data reveal a complex, multicomponent response that on the surface points to an unconventional metallic state in this material. Via a comparison with photoemission, the anomalous optical response may be attributed to an unexpectedly strong interband transition near 180 meV between spin-orbit coupled bands that are nearly parallel along ΓX. This spin-orbit coupling effect is shown to occur in a number of related metallic ruthenates and explains the previously puzzling optical properties reported for these materials.
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Affiliation(s)
- Luke J Sandilands
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
- Measurement Science and Standards, National Research Council Canada, Ottawa, Ottawa K1A 0R6 Canada
| | - Wonshik Kyung
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
| | - So Yeun Kim
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
| | - J Son
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
| | - J Kwon
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
| | - T D Kang
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
| | - Y Yoshida
- National Institute of Advanced Industrial Science and Technology, Tsukuba 305-8568, Japan
| | - S J Moon
- Department of Physics, Hanyang University, Seoul 04763, Republic of Korea
| | - C Kim
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
| | - Tae Won Noh
- Center for Correlated Electron Systems, Institute for Basic Science, Seoul 08826, Republic of Korea
- Department of Physics and Astronomy, Seoul National University, Seoul 08826, Republic of Korea
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Cho J, Kim Y, Ahn H, I H, Son J. P3.16-006 Impact of Limited Resection or Omitted Adjuvant Therapy in Patients with Pathologic Stage II and III Non-Small-Cell Lung Cancer. J Thorac Oncol 2017. [DOI: 10.1016/j.jtho.2017.09.1812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Cho J, Kim Y, Ahn H, I H, Son J. P1.16-001 Characteristics of Resected Lung Cancer in Patients Aged Under 60: A Single–Center Experience. J Thorac Oncol 2017. [DOI: 10.1016/j.jtho.2017.09.1054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Lee J, Rho J, Son J, Choi C. P3.02-088 Enhanced Glycolysis Is Critical for Maintaining Inactivation of JNK and Stability of EGFR Leading to the Survival of EGFR-Mutant Lung Cancer Cells. J Thorac Oncol 2017. [DOI: 10.1016/j.jtho.2017.09.1617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Suh DS, Kang KT, Son J, Kwon OR, Baek C, Koh YG. Computational study on the effect of malalignment of the tibial component on the biomechanics of total knee arthroplasty: A Finite Element Analysis. Bone Joint Res 2017; 6:623-630. [PMID: 29162607 PMCID: PMC5717075 DOI: 10.1302/2046-3758.611.bjr-2016-0088.r2] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 07/03/2017] [Indexed: 11/10/2022] Open
Abstract
Objectives Malalignment of the tibial component could influence the long-term survival of a total knee arthroplasty (TKA). The object of this study was to investigate the biomechanical effect of varus and valgus malalignment on the tibial component under stance-phase gait cycle loading conditions. Methods Validated finite element models for varus and valgus malalignment by 3° and 5° were developed to evaluate the effect of malalignment on the tibial component in TKA. Maximum contact stress and contact area on a polyethylene insert, maximum contact stress on patellar button and the collateral ligament force were investigated. Results There was greater total contact stress in the varus alignment than in the valgus, with more marked difference on the medial side. An increase in ligament force was clearly demonstrated, especially in the valgus alignment and force exerted on the medial collateral ligament also increased. Conclusion These results highlight the importance of accurate surgical reconstruction of the coronal tibial alignment of the knee joint. Varus and valgus alignments will influence wear and ligament stability, respectively in TKA. Cite this article: D-S. Suh, K-T. Kang, J. Son, O-R. Kwon, C. Baek, Y-G. Koh. Computational study on the effect of malalignment of the tibial component on the biomechanics of total knee arthroplasty: A Finite Element Analysis. Bone Joint Res 2017;6:623–630. DOI: 10.1302/2046-3758.611.BJR-2016-0088.R2.
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Affiliation(s)
- D-S Suh
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeongro, Seocho-gu, Seoul, 06698, Republic of Korea
| | - K-T Kang
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - J Son
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - O-R Kwon
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeongro, Seocho-gu, Seoul, 06698, Republic of Korea
| | - C Baek
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeongro, Seocho-gu, Seoul, 06698, Republic of Korea
| | - Y-G Koh
- Department of Orthopaedic Surgery, Joint Reconstruction Center, Yonsei Sarang Hospital, 10 Hyoryeongro, Seocho-gu, Seoul, 06698, Republic of Korea
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Cho J, Kim Y, Ahn H, I H, Son J. P2.16-011 Unsuspectedly Detected Isolated Fibrinogen Deficiency in a Patient with Lung Adenocarcinoma after Surgery. J Thorac Oncol 2017. [DOI: 10.1016/j.jtho.2017.09.1420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Park M, Seo H, Kim B, Son J, Liu K, Park B, Kim M, Hong S. 123 The fatty-acid chain length of ceramides is negatively affected by chronic UV exposure. J Invest Dermatol 2017. [DOI: 10.1016/j.jid.2017.07.433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Kim H, Choi Y, Son J, Cho Y, Chung B, Park C. 142 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) regulates the expression of AhR-related factors(AhR, ARNT, CYP1A1), and cytokines in peripheral blood mononuclear cells and changes in differentiation of CD4+ T cells from healthy subjects, patients with atopic dermatitis and psoriasis. J Invest Dermatol 2017. [DOI: 10.1016/j.jid.2017.07.452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Koh YG, Son J, Kwon SK, Kim HJ, Kwon OR, Kang KT. Preservation of kinematics with posterior cruciate-, bicruciate- and patient-specific bicruciate-retaining prostheses in total knee arthroplasty by using computational simulation with normal knee model. Bone Joint Res 2017; 6:557-565. [PMID: 28947604 PMCID: PMC5631000 DOI: 10.1302/2046-3758.69.bjr-2016-0250.r1] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Accepted: 06/30/2017] [Indexed: 12/11/2022] Open
Abstract
Objectives Preservation of both anterior and posterior cruciate ligaments in total knee arthroplasty (TKA) can lead to near-normal post-operative joint mechanics and improved knee function. We hypothesised that a patient-specific bicruciate-retaining prosthesis preserves near-normal kinematics better than standard off-the-shelf posterior cruciate-retaining and bicruciate-retaining prostheses in TKA. Methods We developed the validated models to evaluate the post-operative kinematics in patient-specific bicruciate-retaining, standard off-the-shelf bicruciate-retaining and posterior cruciate-retaining TKA under gait and deep knee bend loading conditions using numerical simulation. Results Tibial posterior translation and internal rotation in patient-specific bicruciate-retaining prostheses preserved near-normal kinematics better than other standard off-the-shelf prostheses under gait loading conditions. Differences from normal kinematics were minimised for femoral rollback and internal-external rotation in patient-specific bicruciate-retaining, followed by standard off-the-shelf bicruciate-retaining and posterior cruciate-retaining TKA under deep knee bend loading conditions. Moreover, the standard off-the-shelf posterior cruciate-retaining TKA in this study showed the most abnormal performance in kinematics under gait and deep knee bend loading conditions, whereas patient-specific bicruciate-retaining TKA led to near-normal kinematics. Conclusion This study showed that restoration of the normal geometry of the knee joint in patient-specific bicruciate-retaining TKA and preservation of the anterior cruciate ligament can lead to improvement in kinematics compared with the standard off-the-shelf posterior cruciate-retaining and bicruciate-retaining TKA. Cite this article: Y-G. Koh, J. Son, S-K. Kwon, H-J. Kim, O-R. Kwon, K-T. Kang. Preservation of kinematics with posterior cruciate-, bicruciate- and patient-specific bicruciate-retaining prostheses in total knee arthroplasty by using computational simulation with normal knee model. Bone Joint Res 2017;6:557–565. DOI: 10.1302/2046-3758.69.BJR-2016-0250.R1.
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Affiliation(s)
- Y-G Koh
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - J Son
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - S-K Kwon
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - H-J Kim
- Spine Center and Department of Orthopaedic Surgery, Seoul National University College of Medicine and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beongil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, South Korea
| | - O-R Kwon
- Joint Reconstruction Center, Department of Orthopaedic Surgery, Yonsei Sarang Hospital, 10 Hyoryeong-ro, Seocho-gu, Seoul 06698, South Korea
| | - K-T Kang
- Department of Mechanical Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
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