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Ren L, Liu Y, Tong Y, Cao X, Wu Y. Calcification segmentation based on a different scales superpixels saliency detection algorithm. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:3404-3412. [PMID: 32977997 DOI: 10.1016/j.ultrasmedbio.2020.08.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 07/05/2020] [Accepted: 08/09/2020] [Indexed: 06/11/2023]
Abstract
Accurate detection of breast tumor calcifications is of great significance in assisting doctors' diagnosis to improve the accuracy of breast cancer early detection. In this article, a different scale of superpixels saliency detection algorithm is used to segment calcifications in breast tumor ultrasound images based on a simple linear iterative cluster. First, a multi-scale saliency segmentation algorithm was used to divide the tumor region of different sizes and weak calcification (Wca) was extracted according to uneven gray distribution and texture contrast between regions. Second, based on single-scale superpixel segmentation of the original image, the strong calcification extraction map was calculated by measuring gray value difference and calcification gray distance features. Finally, the final calcification extraction map was obtained by combining the strong and weak calcification extraction maps. The detection algorithm proposed in this article could effectively detect calcifications in breast ultrasound images.
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Affiliation(s)
- Li Ren
- Electronic and Communication Engineering, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China 210003.
| | - Yangyang Liu
- College of Information and Communication Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu, China 211167
| | - Ying Tong
- College of Information and Communication Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu, China 211167
| | - Xuehong Cao
- Electronic and Communication Engineering, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China 210003; College of Information and Communication Engineering, Nanjing Institute of Technology, Nanjing, Jiangsu, China 211167
| | - Yiyun Wu
- Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China 210029
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2
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Compression of CT Images using Contextual Vector Quantization with Simulated Annealing for Telemedicine Application. J Med Syst 2018; 42:218. [DOI: 10.1007/s10916-018-1090-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 09/26/2018] [Indexed: 10/28/2022]
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3
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Cavero E, Alesanco A, Castro L, Montoya J, Lacambra I, Garcia J. SPIHT-Based Echocardiogram Compression: Clinical Evaluation and Recommendations of Use. IEEE J Biomed Health Inform 2013. [DOI: 10.1109/titb.2012.2227336] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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4
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Despeckling of ultrasound images of bone fracture using multiple filtering algorithms. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/j.mcm.2011.07.021] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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5
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Medical ultrasound image compression using contextual vector quantization. Comput Biol Med 2012; 42:743-50. [DOI: 10.1016/j.compbiomed.2012.04.006] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2011] [Revised: 03/07/2012] [Accepted: 04/24/2012] [Indexed: 11/18/2022]
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6
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Kaur L, Chauhan RC, Saxena SC. Joint thresholding and quantizer selection for compression of medical ultrasound images in the wavelet domain. J Med Eng Technol 2009; 30:17-24. [PMID: 16393849 DOI: 10.1080/03091900500037309] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
This paper introduces a simple and efficient technique for compression of medical ultrasound (US) images in the wavelet domain. The statistics of subband wavelet coefficients are modelled using the generalized Gaussian distribution (GGD). By exploiting these statistics, a uniform scalar quantizer is designed which adapts very well to the changing statistics of the signal across various subbands and scales. To increase the quantization performance, a threshold is chosen adaptively to zero-out the insignificant wavelet coefficients in the detail subbands before quantization. A distinctive feature of the proposed technique is that it unifies the two approaches to image adaptive coding: rate-distortion (R-D) optimized quantizer selection and R-D optimal thresholding, in order to increase the compression performance of the coder. The operational R-D criterion used for joint optimization is derived in the minimum description length (MDL) framework. The experimental results show that the joint R-D optimization leads to significant improvement in the compression performance of the proposed coder, named JTQ-WV, over the best state-of-the-art image coder, SPIHT. For example, the coding of US images at 0.25 bpp by JTQ-WV yields a PSNR gain of 1.0 dB over the benchmark SPIHT.
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Affiliation(s)
- L Kaur
- Sant Longowal Institute of Engineering & Technology, Sangrur, (Pb.), India.
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7
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Zacharaki EI, Shen D, Lee SK, Davatzikos C. ORBIT: a multiresolution framework for deformable registration of brain tumor images. IEEE TRANSACTIONS ON MEDICAL IMAGING 2008; 27:1003-17. [PMID: 18672419 PMCID: PMC2832332 DOI: 10.1109/tmi.2008.916954] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
A deformable registration method is proposed for registering a normal brain atlas with images of brain tumor patients. The registration is facilitated by first simulating the tumor mass effect in the normal atlas in order to create an atlas image that is as similar as possible to the patient's image. An optimization framework is used to optimize the location of tumor seed as well as other parameters of the tumor growth model, based on the pattern of deformation around the tumor region. In particular, the optimization is implemented in a multiresolution and hierarchical scheme, and it is accelerated by using a principal component analysis (PCA)-based model of tumor growth and mass effect, trained on a computationally more expensive biomechanical model. Validation on simulated and real images shows that the proposed registration framework, referred to as ORBIT (optimization of tumor parameters and registration of brain images with tumors), outperforms other available registration methods particularly for the regions close to the tumor, and it has the potential to assist in constructing statistical atlases from tumor-diseased brain images.
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Affiliation(s)
- Evangelia I. Zacharaki
- Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, 3600 Market Street, Philadelphia, PA 19104 USA
| | - Dinggang Shen
- Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Seung-Koo Lee
- Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Christos Davatzikos
- Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 USA
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8
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Chen YY. Medical image compression using DCT-based subband decomposition and modified SPIHT data organization. Int J Med Inform 2007; 76:717-25. [PMID: 16931130 DOI: 10.1016/j.ijmedinf.2006.07.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2005] [Revised: 07/03/2006] [Accepted: 07/09/2006] [Indexed: 11/20/2022]
Abstract
OBJECTIVE The work proposed a novel bit-rate-reduced approach for reducing the memory required to store a remote diagnosis and rapidly transmission it. METHOD In the work, an 8x8 Discrete Cosine Transform (DCT) approach is adopted to perform subband decomposition. Modified set partitioning in hierarchical trees (SPIHT) is then employed to organize data and entropy coding. The translation function can store the detailed characteristics of an image. A simple transformation to obtain DCT spectrum data in a single frequency domain decomposes the original signal into various frequency domains that can further compressed by wavelet-based algorithm. In this scheme, insignificant DCT coefficients that correspond to a particular spatial location in the high-frequency subbands can be employed to reduce redundancy by applying a proposed combined function in association with the modified SPIHT. RESULTS AND CONCLUSIONS Simulation results showed that the embedded DCT-CSPIHT image compression reduced the computational complexity to only a quarter of the wavelet-based subband decomposition, and improved the quality of the reconstructed medical image as given by both the peak signal-to-noise ratio (PSNR) and the perceptual results over JPEG2000 and the original SPIHT at the same bit rate. Additionally, since 8x8 fast DCT hardware implementation being commercially available, the proposed DCT-CSPIHT can perform well in high speed image coding and transmission.
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Affiliation(s)
- Yen-Yu Chen
- Department of Information Management, ChengChou Institute of Technology, 6, Line 2, Sec 3, Shan-Chiao Rd., Yuanlin, Changhwa, Taiwan.
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Giakoumaki A, Pavlopoulos S, Koutsouris D. A multiple watermarking scheme applied to medical image management. CONFERENCE PROCEEDINGS : ... ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL CONFERENCE 2007; 2004:3241-4. [PMID: 17270971 DOI: 10.1109/iembs.2004.1403912] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Digital watermarking is a recently emerged research area, which has the potential of providing alternative/complementary solutions for a number of issues relating to medical data management and distribution. The present paper aims to reveal the perspectives of digital watermarking in health information systems, and proposes a wavelet-based multiple watermarking scheme that addresses the issues of medical data protection, archiving, and retrieval, as well as of origin and data authentication. The scheme applies multiple watermarking in medical images, and embeds in them the physician's digital signature, patient's personal and examination data, keywords for image retrieval, and a reference watermark for the purpose of data integrity control. The experimental results demonstrate the efficiency and transparency of the watermarking scheme, which conforms to the strict limitations that apply to regions of diagnostic significance.
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Affiliation(s)
- A Giakoumaki
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, Greece
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Giakoumaki A, Pavlopoulos S, Koutsouris D. Multiple image watermarking applied to health information management. ACTA ACUST UNITED AC 2006; 10:722-32. [PMID: 17044406 DOI: 10.1109/titb.2006.875655] [Citation(s) in RCA: 146] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Information technology advances have brought forth new challenges in healthcare information management, due to the vast amount of medical data that needs to be efficiently stored, retrieved, and distributed, and the increased security threats that explicitly have to be addressed. The paper discusses the perspectives of digital watermarking in a range of medical data management and distribution issues, and proposes a complementary and/or alternative tool that simultaneously addresses medical data protection, archiving, and retrieval, as well as source and data authentication. The scheme imperceptibly embeds in medical images multiple watermarks conveying patient's personal and examination data, keywords for information retrieval, the physician's digital signature for authentication, and a reference message for data integrity control. Experimental results indicate the efficiency and transparency of the scheme, which conforms to the strict requirements that apply to regions of diagnostic significance.
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Affiliation(s)
- Aggeliki Giakoumaki
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
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11
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Kaur L, Chauhan RC, Saxena SC. Wavelet based compression of medical ultrasound images using vector quantization. J Med Eng Technol 2006; 30:128-33. [PMID: 16772214 DOI: 10.1080/03091900500235705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
In this paper, an efficient technique for compression of medical ultrasound (US) images is proposed. The technique is based on wavelet transform of the original image combined with vector quantization (VQ) of high-energy subbands using the LBG algorithm. First, we analyse the statistical behaviour of wavelet coefficients in US images across various subbands and scales. The analysis show that most of the image energy is concentrated in one of the detail subband, either in the vertical detail subband (most of the time) or in the horizontal subband. The other two subbands at each decomposition level contribute negligibly to the total image energy. Then, by exploiting this statistical analysis, a low-complexity image coder is designed, which applies VQ only to the highest energy subband while discarding the other detail subbands at each level of decomposition. The coder is tested on a series of abdominal and uterus greyscale US images. The experimental results indicate that the proposed method clearly outperforms the JPEG2000 (Joint Photographers Expert Group) encoder both qualitatively and quantitatively. For example, without using any entropy coder, the proposed method yields a peak signal to noise ratio gain of 0.2 dB to 1.2 dB over JPEG2000 on medical US images.
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Affiliation(s)
- L Kaur
- Sant Longowal Institute of Engineering & Technology, Sangrur, Punjab, 148106, India.
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13
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Kassim AA, Yan P, Lee WS, Sengupta K. Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE : A PUBLICATION OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY 2005; 9:132-8. [PMID: 15787015 DOI: 10.1109/titb.2004.838376] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.
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Affiliation(s)
- Ashraf A Kassim
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 119260, Singapore.
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Chen YY, Tai SC. Enhancing ultrasound images by morphology filter and eliminating ringing effect. Eur J Radiol 2005; 53:293-305. [PMID: 15664295 DOI: 10.1016/j.ejrad.2004.02.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2003] [Revised: 02/08/2004] [Accepted: 02/10/2004] [Indexed: 11/23/2022]
Abstract
Various medical image compression techniques have been proposed for accelerating image propagation in many applications. JPEG2000 is a new generation technique that can encode near lossless ultrasound images at medium bit-rate with diagnostically acceptable quality. Because the coder of JPEG2000 is based on wavelet transform, the reconstructed image will contain some ringing artifacts. Some de-ringing algorithm must be applied to enhance image quality. This study presents quad-tree decomposition and a set of morphological filters for reducing the ringing artifacts of ultrasound images. Specifically, the presented morphological filters use eight predefined morphological operations, including four structuring elements (SE) that include both dilation and erosion. The proposed voting strategy can be used to select the morphological filter for each block to optimize decoded image quality. Image quality can be enhanced by applying the appropriate morphological filter to each block. Experimental results demonstrate that the proposed technique enhances reconstructed ultrasound image quality compared to JPEG2000 at the same bit-rate in terms of both PSNR and the perceptual results.
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Affiliation(s)
- Yen-Yu Chen
- Data Compression and Multimedia Communication Laboratory, Department of Electrical Engineering, National Cheng Kung University, No. 1 Ta Hsueh Road, Tainan 701, Taiwan, ROC.
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Kaur L, Chauhan RC, Saxena SC. Space-frequency quantiser design for ultrasound image compression based on minimum description length criterion. Med Biol Eng Comput 2005; 43:33-9. [PMID: 15742717 DOI: 10.1007/bf02345120] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
The paper addresses the problem of how the spatial quantisation mode and subband adaptive uniform scalar quantiser can be jointly optimised in the minimum description length (MDL) framework for compression of ultrasound images. It has been shown that the statistics of wavelet coefficients in the medical ultrasound (US) image can be better approximated by the generalised Student t-distribution. By combining these statistics with the operational rate-distortion (RD) criterion, a space-frequency quantiser (SFQ) called the MDL-SFQ was designed, which used an efficient zero-tree quantisation technique for zeroing out the tree-structured sets of wavelet coefficients and an adaptive scalar quantiser to quantise the non-zero coefficients. The algorithm used the statistical 'variance of quantisation error' to achieve the different bit-rates ranging from near-lossless to lossy compression. Experimental results showed that the proposed coder outperformed the set partitioning in hierarchical trees (SPIHT) image coder both quantitatively and qualitatively. It yielded an improved compression performance of 1.01 dB over the best zero-tree based coder SPIHIT at 0.25 bits per pixel when averaged over five ultrasound images.
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Affiliation(s)
- L Kaur
- Sant Longowal Institute of Engineering & Technology, Longowal, India.
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