Development and application of a 3D image analysis strategy for focused ion beam - Scanning electron microscopy tomography of porous soft materials

In recent years, the potential of porous soft materials in various device technologies has increased in importance due to applications in fields, such as wearable electronics, medicine, and transient devices. However, understanding the 3-dimensional architecture of porous soft materials at the microscale remains a challenge. Herein, we present a method to structurally analyze soft materials using Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) tomography. Two materials, polymethyl methacrylate (PMMA) membrane and pine wood veneer were chosen as test-cases. FIB-SEM was successfully used to reconstruct the true topography of these materials in 3D. Structural and physical properties were subsequently deduced from the rendered 3D models. The methodology used segmentation, coupled with optimized thresholding, image processing, and reconstruction protocols. The 3D models generated pore size distribution, pore inter-connectivity, tortuosity, thickness, and curvature data. It was shown that FIB-SEM tomography provides both an informative and visual depiction of structure. To evaluate and validate the FIB-SEM reconstructions, porous properties were generated from the physical property analysis techniques, gas adsorption analysis using Brunauer-Emmett-Teller (BET) surface area analysis and mercury intrusion porosimetry (MIP) analysis. In general, the data obtained from the FIB-SEM reconstructions was well-matched with the physical data. RESEARCH HIGHLIGHTS: Porous specimens of both synthetic and biological nature, a poly(methyl methacrylate) membrane and a pine veneer respectively, are reconstructed via FIB-SEM tomography without resin-embedding. Different thresholding and reconstruction methods are explored whereby shadowing artifacts are present with the aid of free open-source software. Reconstruction data is compared to physical data: MIP, gas adsorption isotherms which are analyzed via BET and Barrett-Joyner-Halenda (BJH) analysis to yield a full picture of the materials.

RT-SRTS: Angle-agnostic real-time simultaneous 3D reconstruction and tumor segmentation from single X-ray projection

Radiotherapy is one of the primary treatment methods for tumors, but the organ movement caused by respiration limits its accuracy. Recently, 3D imaging from a single X-ray projection has received extensive attention as a promising approach to address this issue. However, current methods can only reconstruct 3D images without directly locating the tumor and are only validated for fixed-angle imaging, which fails to fully meet the requirements of motion control in radiotherapy. In this study, a novel imaging method RT-SRTS is proposed which integrates 3D imaging and tumor segmentation into one network based on multi-task learning (MTL) and achieves real-time simultaneous 3D reconstruction and tumor segmentation from a single X-ray projection at any angle. Furthermore, the attention enhanced calibrator (AEC) and uncertain-region elaboration (URE) modules have been proposed to aid feature extraction and improve segmentation accuracy. The proposed method was evaluated on fifteen patient cases and compared with three state-of-the-art methods. It not only delivers superior 3D reconstruction but also demonstrates commendable tumor segmentation results. Simultaneous reconstruction and segmentation can be completed in approximately 70 ms, significantly faster than the required time threshold for real-time tumor tracking. The efficacies of both AEC and URE have also been validated in ablation studies. The code of work is available at https://github.com/ZywooSimple/RT-SRTS.

Ultrasonic mapping of midpalatal suture - An ex-vivo study

OBJECTIVE

Rapid maxillary expansion is a common orthodontic procedure to correct maxillary constriction. Assessing the midpalatal suture (MPS) expansion plays a crucial role in treatment planning to determine its effectiveness. The objectives of this preliminary investigation are to demonstrate a proof of concept that the palatal bone underlying the rugae can be clearly imaged by ultrasound (US) and the reconstructed axial view of the US image accurately maps the MPS patency.

METHODS

An ex-vivo US scanning was conducted on the upper jawbones of two piglet's carcasses before and after the creation of bone defects, which simulated the suture opening. The planar images were processed to enhance bone intensity distribution before being orderly stacked to fuse into a volume. Graph-cut segmentation was applied to delineate the palatal bone to generate a bone volume. The accuracy of the reconstructed bone volume and the suture opening was validated by the µCT data used as the ground truth and compared with CBCT data as the clinical standard. Also included in the comparison is the rugae thickness. Correlation and Bland-Altman plots were used to test the agreement between the two methods: US versus µCT/CBCT.

RESULTS

The reconstruction of the US palatal bone volumes was accurate based on surface topography comparison with a mean error of 0.19 mm for pre-defect and 0.15 mm and 0.09 mm for post-defect models of the two samples, respectively when compared with µCT volumes. A strong correlation (R2 ≥ 0.99) in measuring MPS expansion was found between US and µCT/ CBCT with MADs of less than 0.05 mm, 0.11 mm and 0.23 mm for US, µCT and CBCT, respectively.

CONCLUSIONS

It was possible to axially image the MPS opening and rugae thickness accurately using high-frequency ultrasound.

CLINICAL SIGNIFICANCE

This study introduces an ionizing radiation-free, low-cost, and portable technique to accurately image a difficult part of oral cavity anatomy. The advantages of conceivable visualization could promise a successful clinical examination of MPS to support the predictable treatment outcome of maxillary transverse deficiency.

Efficient EndoNeRF reconstruction and its application for data-driven surgical simulation

PURPOSE

The healthcare industry has a growing need for realistic modeling and efficient simulation of surgical scenes. With effective models of deformable surgical scenes, clinicians are able to conduct surgical planning and surgery training on scenarios close to real-world cases. However, a significant challenge in achieving such a goal is the scarcity of high-quality soft tissue models with accurate shapes and textures. To address this gap, we present a data-driven framework that leverages emerging neural radiance field technology to enable high-quality surgical reconstruction and explore its application for surgical simulations.

METHOD

We first focus on developing a fast NeRF-based surgical scene 3D reconstruction approach that achieves state-of-the-art performance. This method can significantly outperform traditional 3D reconstruction methods, which have failed to capture large deformations and produce fine-grained shapes and textures. We then propose an automated creation pipeline of interactive surgical simulation environments through a closed mesh extraction algorithm.

RESULTS

Our experiments have validated the superior performance and efficiency of our proposed approach in surgical scene 3D reconstruction. We further utilize our reconstructed soft tissues to conduct FEM and MPM simulations, showcasing the practical application of our method in data-driven surgical simulations.

CONCLUSION

We have proposed a novel NeRF-based reconstruction framework with an emphasis on simulation purposes. Our reconstruction framework facilitates the efficient creation of high-quality surgical soft tissue 3D models. With multiple soft tissue simulations demonstrated, we show that our work has the potential to benefit downstream clinical tasks, such as surgical education.

Application of a novel deep learning-based 3D videography workflow to bat flight

Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increasing framerates and numbers of cameras. Here, we present a workflow that combines deep learning-powered automatic digitization with filtering and correction of mislabeled points using quality metrics from deep learning and 3D reconstruction. We tested our workflow using a particularly challenging scenario: bat flight. First, we documented four bats flying steadily in a 2 m3 wind tunnel test section. Wing kinematic parameters resulting from manually digitizing bats with markers applied to anatomical landmarks were not significantly different from those resulting from applying our workflow to the same bats without markers for five out of six parameters. Second, we compared coordinates from manual digitization against those yielded via our workflow for bats flying freely in a 344 m3 enclosure. Average distance between coordinates from our workflow and those from manual digitization was less than a millimeter larger than the average human-to-human coordinate distance. The improved efficiency of our workflow has the potential to increase the scalability of studies on animal flight biomechanics.

Laryngeal surface reconstructions from monocular endoscopic videos: a structure from motion pipeline for periodic deformations

PURPOSE

Surface reconstructions from laryngoscopic videos have the potential to assist clinicians in diagnosing, quantifying, and monitoring airway diseases using minimally invasive techniques. However, tissue movements and deformations make these reconstructions challenging using conventional pipelines.

METHODS

To facilitate such reconstructions, we developed video frame pre-filtering and featureless dense matching steps to enhance the Alicevision Meshroom SfM pipeline. Time and the anterior glottic angle were used to approximate the rigid state of the airway and to collect frames with different camera poses. Featureless dense matches were tracked with a correspondence transformer across subsets of images to extract matched points that could be used to estimate the point cloud and reconstructed surface. The proposed pipeline was tested on a simulated dataset under various conditions like illumination and resolution as well as real laryngoscopic videos.

RESULTS

Our pipeline was able to reconstruct the laryngeal region based on 4, 8, and 16 images obtained from simulated and real patient exams. The pipeline was robust to sparse inputs, blur, and extreme lighting conditions, unlike the Meshroom pipeline which failed to produce a point cloud for 6 of 15 simulated datasets.

CONCLUSION

The pre-filtering and featureless dense matching modules specialize the conventional SfM pipeline to handle the challenging laryngoscopic examinations, directly from patient videos. These 3D visualizations have the potential to improve spatial understanding of airway conditions.

A semiparametric Gaussian mixture model for chest CT-based 3D blood vessel reconstruction

Computed tomography (CT) has been a powerful diagnostic tool since its emergence in the 1970s. Using CT data, 3D structures of human internal organs and tissues, such as blood vessels, can be reconstructed using professional software. This 3D reconstruction is crucial for surgical operations and can serve as a vivid medical teaching example. However, traditional 3D reconstruction heavily relies on manual operations, which are time-consuming, subjective, and require substantial experience. To address this problem, we develop a novel semiparametric Gaussian mixture model tailored for the 3D reconstruction of blood vessels. This model extends the classical Gaussian mixture model by enabling nonparametric variations in the component-wise parameters of interest according to voxel positions. We develop a kernel-based expectation-maximization algorithm for estimating the model parameters, accompanied by a supporting asymptotic theory. Furthermore, we propose a novel regression method for optimal bandwidth selection. Compared to the conventional cross-validation-based (CV) method, the regression method outperforms the CV method in terms of computational and statistical efficiency. In application, this methodology facilitates the fully automated reconstruction of 3D blood vessel structures with remarkable accuracy.

3D reconstruction and multi-omics analysis reveal a unique pattern of embryogenesis in Ginkgo biloba

Ginkgo (Ginkgo biloba L.) is one of the earliest extant species in seed plant phylogeny. Embryo development patterns can provide fundamental evidence for the origin, evolution, and adaptation of seeds. However, the architectural and morphological dynamics during embryogenesis in Ginkgo biloba (G. biloba) remain elusive. Herein, we obtained over 2200 visual slices from three stages of embryo development using micro-computed tomography imaging with improved staining methods. Based on 3D spatio-temporal pattern analysis, we found that a shoot apical meristem with seven highly differentiated leaf primordia, including apical and axillary leaf buds, is present in mature Ginkgo embryos. 3D rendering from the front, top, and side views showed two separate transport systems of tracheids located in the hypocotyl and cotyledon, representing a unique pattern of embryogenesis. Furthermore, the morphological dynamic analysis of secretory cavities indicated their strong association with cotyledons during development. In addition, we identified genes GbLBD25a (lateral organ boundaries domain 25a), GbCESA2a (cellulose synthase 2a), GbMYB74c (myeloblastosis 74c), GbPIN2 (PIN-FORMED 2) associated with vascular development regulation, and GbWRKY1 (WRKYGOK 1), GbbHLH12a (basic helix-loop-helix 12a), GbJAZ4 (jasmonate zim-domain 4) potentially involved in the formation of secretory cavities. Moreover, we found that flavonoid accumulation in mature embryos could enhance post-germinative growth and seedling establishment in harsh environments. Our 3D spatial reconstruction technique combined with multi-omics analysis opens avenues for investigating developmental architecture and molecular mechanisms during embryogenesis and lays the foundation for evolutionary studies of embryo development and maturation.

3D reconstruction of a gastrulating human embryo

Progress in understanding early human development has been impeded by the scarcity of reference datasets from natural embryos, particularly those with spatial information during crucial stages like gastrulation. We conducted high-resolution spatial transcriptomics profiling on 38,562 spots from 62 transverse sections of an intact Carnegie stage (CS) 8 human embryo. From this spatial transcriptomic dataset, we constructed a 3D model of the CS8 embryo, in which a range of cell subtypes are identified, based on gene expression patterns and positional register, along the anterior-posterior, medial-lateral, and dorsal-ventral axis in the embryo. We further characterized the lineage trajectories of embryonic and extra-embryonic tissues and associated regulons and the regionalization of signaling centers and signaling activities that underpin lineage progression and tissue patterning during gastrulation. Collectively, the findings of this study provide insights into gastrulation and post-gastrulation development of the human embryo.

Detection of early pulmonary emphysema by multi-contrast x-ray Talbot-Lau interferometer

BACKGROUND

Pulmonary emphysema is a part of chronic obstructive pulmonary disease, which is an irreversible chronic respiratory disease. In order to avoid further damage to lung tissue, early diagnosis and treatment of pulmonary emphysema is essential.

PURPOSE

Early pulmonary emphysema diagnosis is difficult with conventional radiographic imaging. Recently, x-ray phase contrast imaging has proved to be an effective and promising imaging strategy for soft tissue, due to its high sensitivity and multi-contrast. The aim of this study is to diagnose pulmonary emphysema early utilizing an x-ray Talbot-Lau interferometer (TLI).

METHODS

We successfully established the mouse model of emphysema by porcine pancreatic elastase treatment, and then used the established x-ray TLI to perform imaging experiments on the mice with different treatment time. The traditional absorption CT and phase contrast CT were obtained simultaneously through TLI. The CT results and histopathology of mice lung in different treatment time were quantitatively analyzed.

RESULTS

By imaging mice lungs, it can be found that phase contrast has higher sensitivity than absorption contrast in early pulmonary emphysema. The results show that the phase contrast signal could distinguish the pulmonary emphysema earlier than the conventional attenuation signal, which can be consistent with histological images. Through the quantitative analysis of pathological section and phase contrast CT, it can be found that there is a strong linear correlation.

CONCLUSIONS

In this study, we quantitatively analyze mean linear intercept of histological sections and CT values of mice. The results show that the phase contrast signal has higher imaging sensitivity than the attenuation signal. X-ray TLI multi-contrast imaging is proved as a potential diagnostic method for early pulmonary emphysema in mice.

3D reconstruction of the mouse cochlea from scRNA-seq data suggests morphogen-based principles in apex-to-base specification

In the mammalian auditory system, frequency discrimination depends on numerous morphological and physiological properties of the organ of Corti, which gradually change along the apex-to-base (tonotopic) axis of the organ. For example, the basilar membrane stiffness changes tonotopically, thus affecting the tuning properties of individual hair cells. At the molecular level, those frequency-specific characteristics are mirrored by gene expression gradients; however, the molecular mechanisms controlling tonotopic gene expression in the mouse cochlea remain elusive. Through analyzing single-cell RNA sequencing (scRNA-seq) data from E12.5 and E14.5 time points, we predicted that morphogens, rather than a cell division-associated mechanism, confer spatial identity in the extending cochlea. Subsequently, we reconstructed the developing cochlea in 3D space from scRNA-seq data to investigate the molecular pathways mediating positional information. The retinoic acid (RA) and hedgehog pathways were found to form opposing apex-to-base gradients, and functional interrogation using mouse cochlear explants suggested that both pathways jointly specify the longitudinal axis.

A robust transformer-based pipeline of 3D cell alignment, denoise and instance segmentation on electron microscopy sequence images

Germline cells are critical for transmitting genetic information to subsequent generations in biological organisms. While their differentiation from somatic cells during embryonic development is well-documented in most animals, the regulatory mechanisms initiating plant germline cells are not well understood. To thoroughly investigate the complex morphological transformations of their ultrastructure over developmental time, nanoscale 3D reconstruction of entire plant tissues is necessary, achievable exclusively through electron microscopy imaging. This paper presents a full-process framework designed for reconstructing large-volume plant tissue from serial electron microscopy images. The framework ensures end-to-end direct output of reconstruction results, including topological networks and morphological analysis. The proposed 3D cell alignment, denoise, and instance segmentation pipeline (3DCADS) leverages deep learning to provide a cell instance segmentation workflow for electron microscopy image series, ensuring accurate and robust 3D cell reconstructions with high computational efficiency. The pipeline involves five stages: the registration of electron microscopy serial images; image enhancement and denoising; semantic segmentation using a Transformer-based neural network; instance segmentation through a supervoxel-based clustering algorithm; and an automated analysis and statistical assessment of the reconstruction results, with the mapping of topological connections. The 3DCADS model's precision was validated on a plant tissue ground-truth dataset, outperforming traditional baseline models and deep learning baselines in overall accuracy. The framework was applied to the reconstruction of early meiosis stages in the anthers of Arabidopsis thaliana, resulting in a topological connectivity network and analysis of morphological parameters and characteristics of cell distribution. The experiment underscores the 3DCADS model's potential for biological tissue identification and its significance in quantitative analysis of plant cell development, crucial for examining samples across different genetic phenotypes and mutations in plant development. Additionally, the paper discusses the regulatory mechanisms of Arabidopsis thaliana's germline cells and the development of stamen cells before meiosis, offering new insights into the transition from somatic to germline cell fate in plants.

Cost-effective 3D documentation device in forensic medicine

3D documentation in forensics and forensic medicine is being introduced more frequently in various institutes around the world. However, several institutes lack capacity in finances as well as staff to perform 3D documentations regularly. This technical paper aims to present a 3D documentation device that is low cost and easy to use and is a viable entry level solution for forensic medical departments. For this the small single-board computer Raspberry Pi 4 was used in conjunction with its high quality (HQ) camera module to create the 3DLamp - a flexible, low cost and easy to use documentation device. Besides a detailed description of the device this paper also presents four case examples where a 3D documentation was performed and analyses the acquired data and the created 3D models. It was found that the device returns feasible 3D models that appear usable for forensic 3D reconstructions.

Linea alba 3D morphometric variability by CT scan exploration

PURPOSE

The width of the Linea alba, which is often gauged by inter-rectus distance, is a key risk factor for incisional hernia and recurrence. Previous studies provided limited descriptions with no consideration for width, location variability, or curvature. We aimed to offer a comprehensive 3D anatomical analysis of the Linea alba, emphasizing its variations across diverse demographics.

METHODS

Using open source software, 2D sagittal plane and 3D reconstructions were performed on 117 patients' CT scans. Linea alba length, curvature assessed by the sagitta (the longest perpendicular segment between xipho-pubic line and the Linea alba), and continuous width along the height were measured.

RESULTS

The Linea alba had a rhombus shape, with a maximum width at the umbilicus of 4.4 ± 1.9 cm and a larger width above the umbilicus than below. Its length was 37.5 ± 3.6 cm, which increased with body mass index (BMI) (p < 0.001), and was shorter in women (p < 0.001). The sagitta was 2.6 ± 2.2 cm, three times higher in the obese group (p < 0.001), majorated with age (p = 0.009), but was independent of gender (p = 0.212). Linea alba width increased with both age and BMI (p < 0.001-p = 0.002), being notably wider in women halfway between the umbilicus and pubis (p = 0.007).

CONCLUSION

This study provides an exhaustive 3D description of Linea alba's anatomical variability, presenting new considerations for curvature. This method provides a patient-specific anatomy description of the Linea alba. Further studies are needed to determine whether 3D reconstruction correlates with pathologies, such as hernias and diastasis recti.

Morphological heterogeneity of neurons in the human central amygdaloid nucleus

The central amygdaloid nucleus (CeA) has an ancient phylogenetic development and functions relevant for animal survival. Local cells receive intrinsic amygdaloidal information that codes emotional stimuli of fear, integrate them, and send cortical and subcortical output projections that prompt rapid visceral and social behavior responses. We aimed to describe the morphology of the neurons that compose the human CeA (N = 8 adult men). Cells within CeA coronal borders were identified using the thionine staining and were further analyzed using the "single-section" Golgi method followed by open-source software procedures for two-dimensional and three-dimensional image reconstructions. Our results evidenced varied neuronal cell body features, number and thickness of primary shafts, dendritic branching patterns, and density and shape of dendritic spines. Based on these criteria, we propose the existence of 12 morphologically different spiny neurons in the human CeA and discuss the variability in the dendritic architecture within cellular types, including likely interneurons. Some dendritic shafts were long and straight, displayed few collaterals, and had planar radiation within the coronal neuropil volume. Most of the sampled neurons showed a few to moderate density of small stubby/wide spines. Long spines (thin and mushroom) were observed occasionally. These novel data address the synaptic processing and plasticity in the human CeA. Our morphological description can be combined with further transcriptomic, immunohistochemical, and electrophysiological/connectional approaches. It serves also to investigate how neurons are altered in neurological and psychiatric disorders with hindered emotional perception, in anxiety, following atrophy in schizophrenia, and along different stages of Alzheimer's disease.

3D reconstruction of events: Search for a spatial correlation between injuries and the geometry of the body discovery site

The aim of the study was to assess the usefulness of analysing visual material in a 3D environment when examining spatial interrelations between the incident participants, tools, and space surrounding the incident site. Such analysis may provide information about the trauma mechanism, which may lead to the determination of probable events. This paper points to the potential of conducting research under 3D environment conditions on the example of a specific criminal incident-a suspected homicide. The aim of the study was to identify possible circumstances of the events with particular emphasis on the mechanism of death and the involvement of third parties. It was performed a comprehensive 3D reconstruction of the elements of the incident using different sources and forms of evidence, and consequently also different imaging, analysis, and synthesis technologies. The resulting 3D reconstruction and animation of the possible events serve to verify the investigative hypotheses. The paper combines a technical description of the research methodology with a forensic commentary, which ultimately creates an integral synthesis of the medicolegal assessment for trial purposes, while presenting the effectiveness of the research methods used. To sum up, the paper presents an experiment carried out under virtual conditions, impossible to execute under real conditions but critical for trial case analysis.

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized Sn clusters and their host pores in carbon nanofiber) during sodiation and desodiation is revealed using a state-of-the-art 3D electron microscopic reconstruction technique. For the first time, the anomalous expansion of Sn clusters after desodiation is observed owing to the aggregation of clusters/single atoms. Pore connectivity is retained despite the anomalous expansion, suggesting inhibition of solid electrolyte interface formation in the sub-2-nm pores. Taking advantage of the built-in nanoconfinement feature, the CNF film with nanometer-sized interconnected pores hosting Sn clusters (≈2 nm) enables high utilization (95% at a high rate of 1 A g-1) of Sn active sites while maintaining an improved initial Coulombic efficiency of 87%. The findings provide insights into electrochemical reactions in a confined space and a guiding principle in electrode design for battery applications.

Topology observing 3D device reconstruction from continuous-sweep limited angle fluoroscopy

BACKGROUND

Minimally invasive procedures usually require navigating a microcatheter and guidewire through endoluminal structures such as blood vessels and airways to sites of the disease. For numerous clinical applications, two-dimensional (2D) fluoroscopy is the primary modality used for real-time image guidance during navigation. However, 2D imaging can pose challenges for navigation in complex structures. Real-time 3D visualization of devices within the anatomic context could provide considerable benefits for these procedures. Continuous-sweep limited angle (CLA) fluoroscopy has recently been proposed to provide a compromise between conventional rotational 3D acquisitions and real-time fluoroscopy.

PURPOSE

The purpose of this work was to develop and evaluate a noniterative 3D device reconstruction approach for CLA fluoroscopy acquisitions, which takes into account endoluminal topology to avoid impossible paths between disconnected branches.

METHODS

The algorithm relies on a static 3D roadmap (RM) of vessels or airways, which may be generated from conventional cone beam CT (CBCT) acquisitions prior to navigation. The RM is converted to a graph representation describing its topology. During catheter navigation, the device is segmented from the live 2D projection images using a deep learning approach from which the centerlines are extracted. Rays from the focal spot to detector pixels representing 2D device points are identified and intersections with the RM are computed. Based on the RM graph, a subset of line segments is selected as candidates to exclude device paths through disconnected branches of the RM. Depth localization for each point along the device is then performed by finding the point closest to the previous 3D reconstruction along the candidate segments. This process is repeated as the projection angle changes for each CLA image frame. The approach was evaluated in a phantom study in which a catheter and guidewire were navigated along five pathways within a complex vessel phantom. The result was compared to static cCBCT acquisitions of the device in the final position.

RESULTS

The average root mean squared 3D distance between CLA reconstruction and reference centerline was1.87 ± 0.30 $1.87 \pm 0.30$ mm. The Euclidean distance at the device tip was2.92 ± 2.35 $2.92 \pm 2.35$ mm. The correct pathway was identified during reconstruction in100 % $100\%$ of frames (n = 1475 $n=1475$ ). The percentage of 3D device points reconstructed inside the 3D roadmap was91.83 ± 2.52 % $91.83 \pm 2.52\%$ with an average distance of0.62 ± 0.30 $0.62 \pm 0.30$ mm between the device points outside the roadmap and the nearest point within the roadmap.

CONCLUSIONS

This study demonstrates the feasibility of reconstructing curvilinear devices such as catheters and guidewires during endoluminal procedures including intravascular and transbronchial interventions using a noniterative reconstruction approach for CLA fluoroscopy. This approach could improve device navigation in cases where the structure of vessels or airways is complex and includes overlapping branches.

UAV-Borne Mapping Algorithms for Low-Altitude and High-Speed Drone Applications

This article presents an analysis of current state-of-the-art sensors and how these sensors work with several mapping algorithms for UAV (Unmanned Aerial Vehicle) applications, focusing on low-altitude and high-speed scenarios. A new experimental construct is created using highly realistic environments made possible by integrating the AirSim simulator with Google 3D maps models using the Cesium Tiles plugin. Experiments are conducted in this high-realism simulated environment to evaluate the performance of three distinct mapping algorithms: (1) Direct Sparse Odometry (DSO), (2) Stereo DSO (SDSO), and (3) DSO Lite (DSOL). Experimental results evaluate algorithms based on their measured geometric accuracy and computational speed. The results provide valuable insights into the strengths and limitations of each algorithm. Findings quantify compromises in UAV algorithm selection, allowing researchers to find the mapping solution best suited to their application, which often requires a compromise between computational performance and the density and accuracy of geometric map estimates. Results indicate that for UAVs with restrictive computing resources, DSOL is the best option. For systems with payload capacity and modest compute resources, SDSO is the best option. If only one camera is available, DSO is the option to choose for applications that require dense mapping results.

Single-Image-Based 3D Reconstruction of Endoscopic Images

A wireless capsule endoscope (WCE) is a medical device designed for the examination of the human gastrointestinal (GI) tract. Three-dimensional models based on WCE images can assist in diagnostics by effectively detecting pathology. These 3D models provide gastroenterologists with improved visualization, particularly in areas of specific interest. However, the constraints of WCE, such as lack of controllability, and requiring expensive equipment for operation, which is often unavailable, pose significant challenges when it comes to conducting comprehensive experiments aimed at evaluating the quality of 3D reconstruction from WCE images. In this paper, we employ a single-image-based 3D reconstruction method on an artificial colon captured with an endoscope that behaves like WCE. The shape from shading (SFS) algorithm can reconstruct the 3D shape using a single image. Therefore, it has been employed to reconstruct the 3D shapes of the colon images. The camera of the endoscope has also been subjected to comprehensive geometric and radiometric calibration. Experiments are conducted on well-defined primitive objects to assess the method's robustness and accuracy. This evaluation involves comparing the reconstructed 3D shapes of primitives with ground truth data, quantified through measurements of root-mean-square error and maximum error. Afterward, the same methodology is applied to recover the geometry of the colon. The results demonstrate that our approach is capable of reconstructing the geometry of the colon captured with a camera with an unknown imaging pipeline and significant noise in the images. The same procedure is applied on WCE images for the purpose of 3D reconstruction. Preliminary results are subsequently generated to illustrate the applicability of our method for reconstructing 3D models from WCE images.

Establishment and preliminary application of personalized three-dimensional reconstruction of thyroid gland with automatic detection of thyroid nodules based on ultrasound videos

PURPOSE

A well display of the spatial location of thyroid nodules in the thyroid is important for surgical path planning and surgeon-patient communication. The aim of this study was to establish a three-dimensional (3D) reconstruction method of the thyroid gland, thyroid nodule, and carotid artery with automatic detection based on two-dimensional (2D) ultrasound videos, and to evaluate its clinical value.

METHODS

Ultrasound videos, including the thyroid gland with nodule, isthmus of thyroid gland, and ipsilateral carotid artery, were recorded. BC-UNet, MTN-Net, and RDPA-U-Net network models were innovatively employed for segmentation of the thyroid glands, the thyroid nodules, and the carotid artery respectively. Marching Cubes algorithm was used for reconstruction, while Laplacian smoothing algorithm was employed to smooth the 3D model surface. Using this model, 20 patients and 15 surgeons completed surveys on the effectiveness of this model for the pre-surgery demonstration of nodule location as well as surgeon-patient communication.

RESULTS

The thyroid gland with nodule, isthmus of gland, and carotid artery were reconstructed and displayed. With the 3D model, the understanding of the spatial location of thyroid nodules improved in all three surgeon groups, eliminating the influence of professional levels. In the patient survey, the patients' understanding of the thyroid nodule location and procedure for surgery were significantly improved. In addition, with the 3D model, the time for doctors to explain to patients was significantly reduced (16.75  vs. 8.85 min, p = 0.001).

CONCLUSION

To our knowledge, this is the first report of constructing a 3D thyroid model using a deep learning technique for personalized thyroid segmentation based on 2D ultrasound videos. The preliminary clinical application showed that it was conducive to the comprehension of the location of thyroid nodules for surgeons and patients, with significant improvement on the efficiency of surgeon-patient communication.

Improving SLAM Techniques with Integrated Multi-Sensor Fusion for 3D Reconstruction

Simultaneous Localization and Mapping (SLAM) poses distinct challenges, especially in settings with variable elements, which demand the integration of multiple sensors to ensure robustness. This study addresses these issues by integrating advanced technologies like LiDAR-inertial odometry (LIO), visual-inertial odometry (VIO), and sophisticated Inertial Measurement Unit (IMU) preintegration methods. These integrations enhance the robustness and reliability of the SLAM process for precise mapping of complex environments. Additionally, incorporating an object-detection network aids in identifying and excluding transient objects such as pedestrians and vehicles, essential for maintaining the integrity and accuracy of environmental mapping. The object-detection network features a lightweight design and swift performance, enabling real-time analysis without significant resource utilization. Our approach focuses on harmoniously blending these techniques to yield superior mapping outcomes in complex scenarios. The effectiveness of our proposed methods is substantiated through experimental evaluation, demonstrating their capability to produce more reliable and precise maps in environments with variable elements. The results indicate improvements in autonomous navigation and mapping, providing a practical solution for SLAM in challenging and dynamic settings.

BSI-MVS: multi-view stereo network with bidirectional semantic information

The basic principle of multi-view stereo (MVS) is to perform 3D reconstruction by extracting depth information from multiple views. Most current SOTA MVS networks are based on Vision Transformer, which usually means expensive computational complexity. To reduce computational complexity and improve depth map accuracy, we propose a MVS network with Bidirectional Semantic Information (BSI-MVS). Firstly, we design a Multi-Level Spatial Pyramid module to generate multiple layers of feature map for extracting multi-scale information. Then we propose a 2D Bidirectional-LSTM module to capture bidirectional semantic information at different time steps in the horizontal and vertical directions, which contains abundant depth information. Finally, cost volumes are built based on various levels of feature maps to optimize the final depth map. We experiment on the DTU and BlendedMVS datasets. The result shows that our network, in terms of overall metrics, surpasses TransMVSNet, CasMVSNet, CVP-MVSNet, and AACVP-MVSNet respectively by 17.84%, 36.42%, 14.96%, and 4.86%, which also shows a noticeable performance enhancement in objective metrics and visualizations.

3-Dimensional Reconstruction From Histopathological Sections: A Systematic Review

Although pathological tissue analysis is typically performed on single 2-dimensional (2D) histologic reference slides, 3-dimensional (3D) reconstruction from a sequence of histologic sections could provide novel opportunities for spatial analysis of the extracted tissue. In this review, we analyze recent works published after 2018 and report information on the extracted tissue types, the section thickness, and the number of sections used for reconstruction. By analyzing the technological requirements for 3D reconstruction, we observe that software tools exist, both free and commercial, which include the functionality to perform 3D reconstruction from a sequence of histologic images. Through the analysis of the most recent works, we provide an overview of the workflows and tools that are currently used for 3D reconstruction from histologic sections and address points for future work, such as a missing common file format or computer-aided analysis of the reconstructed model.

Expansion and Light-Sheet Microscopy for Nanoscale 3D Imaging

Expansion Microscopy (ExM) and Light-Sheet Fluorescence Microscopy (LSFM) are forefront imaging techniques that enable high-resolution visualization of biological specimens. ExM enhances nanoscale investigation using conventional fluorescence microscopes, while LSFM offers rapid, minimally invasive imaging over large volumes. This review explores the joint advancements of ExM and LSFM, focusing on the excellent performance of the integrated modality obtained from the combination of the two, which is refer to as ExLSFM. In doing so, the chemical processes required for ExM, the tailored optical setup of LSFM for examining expanded samples, and the adjustments in sample preparation for accurate data collection are emphasized. It is delve into various specimen types studied using this integrated method and assess its potential for future applications. The goal of this literature review is to enrich the comprehension of ExM and LSFM, encouraging their wider use and ongoing development, looking forward to the upcoming challenges, and anticipating innovations in these imaging techniques.

Application of three-dimensional technology in video-assisted thoracoscopic surgery sublobectomy

Background

Due to the widespread use of imaging techniques, the detection rate of early-stage lung cancer has increased. Video-assisted thoracoscopic surgery (VATS) sublobectomy has emerged as a prominent alternative to lobectomy, offering advantages like reduced resection range, better preservation of lung function, and enhanced postoperative quality of life. However, sublobectomy is more intricate than lobectomy, necessitating a higher level of surgical proficiency and anatomical understanding.

Methods

Three electronic databases were searched to capture relevant studies from January 2016 to March 2023, which related to the application of three-dimensional(3D) technology in VATS sublobectomy.

Results

Currently, clinical departments such as orthopedics, hepatobiliary surgery, and urology have started using 3D technology. This technology is expected to be widely used in thoracic surgery in future. Now 3D technology assists in preoperative planning, intraoperative navigation and doctor-patient communication.

Conclusion

3D technologies, instrumental in locating pulmonary nodules and identifying variations in target lung segmental vessels and bronchi, play pivotal roles in VATS sublobectomy, especially in preoperative planning, intraoperative navigation, and doctor-patient communication. The limitations of 3D technology in clinical application are analyzed, and the future direction of existing 3D technology development is prospected.

Unveiling the Inner Structure of Micrometric Hollow Polymeric Fibers Using Synchrotron X-Ray Nanotomography

In this study, a novel application of synchrotron X-ray nanotomography based on high-resolution full-field transmission X-ray microscopy for characterizing the structure and morphology of micrometric hollow polymeric fibers is presented. By employing postimage analysis using an open-source software such as Tomviz and ImageJ, various key parameters in fiber morphology, including diameter, wall thickness, wall thickness distribution, pore size, porosity, and surface roughness, were assessed. Electrospun polycaprolactone fibers with micrometric diameters and submicrometric features with induced porosity via gas dissolution foaming were used to this aim. The acquired synchrotron X-ray nanotomography data were analyzed using two approaches: 3D tomographic reconstruction and 2D radiographic projection-based analysis. The results of the combination of both approaches demonstrate unique capabilities of this technique, not achievable by other available techniques, allowing for a full characterization of the internal and external morphology and structure of the fibers as well as to obtain valuable qualitative insights into the overall fiber structure.

OCT-based intra-cochlear imaging and 3D reconstruction: ex vivo validation of a robotic platform

PURPOSE

The small size of the cochlea, and its location deeply embedded in thick temporal bone, poses a challenge for intra-cochlear guidance and diagnostics. Current radiological imaging techniques are not able to visualize the cochlear microstructures in detail. Rotational optical coherence tomography (OCT) fibers show great potential for intra-cochlear guidance. The generated images could be used to map, and study, the tiny cochlear microstructures relevant for hearing.

METHODS

This work describes the design of a rotational OCT probe with an outer diameter of 0.9 mm. It further discusses a robotic system, which features a remote center of motion mechanism, dedicated to the probe's positioning, fine manipulation and stable insertion into the cochlear micro-spaces. Furthermore, the necessary calibration steps for 3D reconstruction are described, followed by a detailed quantitative analysis, comparing the 3D reconstructions using a synthetic, 2:1 scaled scala tympani model with a reconstruction from micro-CT, serving as the ground truth. Finally, the potential of the system is demonstrated by scanning a single ex vivo cadaveric human cochlea.

RESULTS

The study investigates five insertions in the same 2:1 scaled tympani model, along with their corresponding 3D reconstruction. The comparison with micro-CT results in an average root-mean-square error of 74.2 µm, a signed distance error of 38.1 µm and a standard deviation of 63.6 µm. The average F-score of the reconstructions, using a distance threshold of 100 and 74.2 µm, resulted in 83.0% and 71.8%, respectively. Insertion in the cadaveric human cochlea showed the challenges for straight insertion, i.e., navigating the hook region.

CONCLUSION

Overall, the system shows great potential for intra-cochlear guidance and diagnostics, due to the system's capability for precise and stable insertion into the basal turn in the scala tympani. The system, combined with the calibration procedure, results in detailed and precise 3D reconstructions.

Silencing NlFAR7 destroyed the pore canals and related structures of the brown planthopper

Fatty acyl-CoA reductase (FAR) is one of the key enzymes, which catalyses the conversion of fatty acyl-CoA to the corresponding alcohols. Among the FAR family members in the brown planthopper (Nilaparvata lugens), NlFAR7 plays a pivotal role in both the synthesis of cuticular hydrocarbons and the waterproofing of the cuticle. However, the precise mechanism by which NlFAR7 influences the formation of the cuticle structure in N. lugens remains unclear. Therefore, this paper aims to investigate the impact of NlFAR7 through RNA interference, transmission electron microscope, focused ion beam scanning electron microscopy (FIB-SEM) and lipidomics analysis. FIB-SEM is employed to reconstruct the three-dimensional (3D) architecture of the pore canals and related cuticle structures in N. lugens subjected to dsNlFAR7 and dsGFP treatments, enabling a comprehensive assessment of changes in the cuticle structures. The results reveal a reduction in the thickness of the cuticle and disruptions in the spiral structure of pore canals, accompanied by widened base and middle diameters. Furthermore, the lipidomics comparison analysis between dsNlFAR7- and dsGFP-treated N. lugens demonstrated that there were 25 metabolites involved in cuticular lipid layer synthesis, including 7 triacylglycerols (TGs), 5 phosphatidylcholines (PCs), 3 phosphatidylethanolamines (PEs) and 2 diacylglycerols (DGs) decreased, and 4 triacylglycerols (TGs) and 4 PEs increased. In conclusion, silencing NlFAR7 disrupts the synthesis of overall lipids and destroys the cuticular pore canals and related structures, thereby disrupting the secretion of cuticular lipids, thus affecting the cuticular waterproofing of N. lugens. These findings give significant attention with reference to further biochemical researches on the substrate specificity of FAR protein, and the molecular regulation mechanisms during N. lugens life cycle.

Seeking arrangements: cell contact as a cleavage-stage biomarker

RESEARCH QUESTION

What can three-dimensional cell contact networks tell us about the developmental potential of cleavage-stage human embryos?

DESIGN

This pilot study was a retrospective analysis of two Embryoscope imaging datasets from two clinics. An artificial intelligence system was used to reconstruct the three-dimensional structure of embryos from 11-plane focal stacks. Networks of cell contacts were extracted from the resulting embryo three-dimensional models and each embryo's mean contacts per cell was computed. Unpaired t-tests and receiver operating characteristic curve analysis were used to statistically analyse mean cell contact outcomes. Cell contact networks from different embryos were compared with identical embryos with similar cell arrangements.

RESULTS

At t4, a higher mean number of contacts per cell was associated with greater rates of blastulation and blastocyst quality. No associations were found with biochemical pregnancy, live birth, miscarriage or ploidy. At t8, a higher mean number of contacts was associated with increased blastocyst quality, biochemical pregnancy and live birth. No associations were found with miscarriage or aneuploidy. Mean contacts at t4 weakly correlated with those at t8. Four-cell embryos fell into nine distinct cell arrangements; the five most common accounted for 97% of embryos. Eight-cell embryos, however, displayed a greater degree of variation with 59 distinct cell arrangements.

CONCLUSIONS

Evidence is provided for the clinical relevance of cleavage-stage cell arrangement in the human preimplantation embryo beyond the four-cell stage, which may improve selection techniques for day-3 transfers. This pilot study provides a strong case for further investigation into spatial biomarkers and three-dimensional morphokinetics.

In Situ Single Particle Reconstruction Reveals 3D Evolution of PtNi Nanocatalysts During Heating

Tailoring nanoparticles' composition and morphology is of particular interest for improving their performance for catalysis. A challenge of this approach is that the nanoparticles' optimized initial structure often changes during use. Visualizing the three dimensional (3D) structural transformation in situ is therefore critical, but often prohibitively difficult experimentally. Although electron tomography provides opportunities for 3D imaging, restrictions in the tilt range of in situ holders together with electron dose considerations limit the possibilities for in situ electron tomography studies. Here, an in situ 3D imaging methodology is presented using single particle reconstruction (SPR) that allows 3D reconstruction of nanoparticles with controlled electron dose and without tilting the microscope stage. This in situ SPR methodology is employed to investigate the restructuring and elemental redistribution within a population of PtNi nanoparticles at elevated temperatures. The atomic structure of PtNi is further examined and a heat-induced transition is found from a disordered to an ordered phase. Changes in structure and elemental distribution are linked to a loss of catalytic activity in the oxygen reduction reaction. The in situ SPR methodology employed here can be extended to a wide range of in situ studies employing not only heating, but gaseous, aqueous, or electrochemical environments to reveal in-operando nanoparticle evolution in 3D.

Computed tomography and three dimensional anatomical study of the liver in the chinchilla (Chinchilla lanigera)

Few instances of neoplastic formations in the liver of chinchillas have been found, even though the species is widely used in different scientific experiments. In the present article we investigate the anatomical features of the chinchilla's liver using CT and three dimension (3D) imaging. For the trials we used 12 (six males and six females) clinically healthy chinchillas all at 18 months of age. The animals were positioned in dorsal recumbency. We used Th8 to L2 vertebrae and the sternum as bone markers for the transverse CT study. The investigated anatomical landmarks for the CT coronal study were the vertebrae, costal arch, soft abdominal wall, diaphragm, stomach and the right kidney. 3D reconstructions were accomplished with a specific imaging software. On transverse and coronal CT images, the chinchilla's liver was composed of lobus hepatis sinister lateralis, 'middle lobe'-without proper Latin term in NAV 2017, lobus hepatis dexter and lobus caudatus. The 'middle lobe' was separated into the 'left middle lobe' and the 'right middle lobe'. Lobus hepatis dexter consisted of lobus hepatis dexter medialis and lobus hepatis dexter lateralis. There was an anatomical relation between the liver, fundus ventriculi and corpus ventriculi. Proc. caudatus was in close contact with the right kidney. Vesica fellea was elongated and ellipsoid. 3D reformatted images confirmed the results obtained by transverse and coronal CT studies. The CT density of the liver in HU was 195.6 ± 73.1. The CT and 3D reconstructed images were visualized at high resolution. This data could be used as a basis for further morphological and imaging studies.

Anatomical organization of the cerebrum of the praying mantis Hierodula membranacea

Many predatory animals, such as the praying mantis, use vision for prey detection and capture. Mantises are known in particular for their capability to estimate distances to prey by stereoscopic vision. While the initial visual processing centers have been extensively documented, we lack knowledge on the architecture of central brain regions, pivotal for sensory motor transformation and higher brain functions. To close this gap, we provide a three-dimensional (3D) reconstruction of the central brain of the Asian mantis, Hierodula membranacea. The atlas facilitates in-depth analysis of neuron ramification regions and aides in elucidating potential neuronal pathways. We integrated seven 3D-reconstructed visual interneurons into the atlas. In total, 42 distinct neuropils of the cerebrum were reconstructed based on synapsin-immunolabeled whole-mount brains. Backfills from the antenna and maxillary palps, as well as immunolabeling of γ-aminobutyric acid (GABA) and tyrosine hydroxylase (TH), further substantiate the identification and boundaries of brain areas. The composition and internal organization of the neuropils were compared to the anatomical organization of the brain of the fruit fly (Drosophila melanogaster) and the two available brain atlases of Polyneoptera-the desert locust (Schistocerca gregaria) and the Madeira cockroach (Rhyparobia maderae). This study paves the way for detailed analyses of neuronal circuitry and promotes cross-species brain comparisons. We discuss differences in brain organization between holometabolous and polyneopteran insects. Identification of ramification sites of the visual neurons integrated into the atlas supports previous claims about homologous structures in the optic lobes of flies and mantises.

A morphofunctional study of the jumping apparatus in globular springtails

Springtails are notable for their jumping apparatus and latch-mediated spring mechanism. The challenge, in the light of the tiny size and rapid movement of these organisms, has been to understand the morphological intricacies of this spring system. This study takes an approach that integrates SEM, MicroCT, cLSM and high-speed video recordings to understand the composition and functionality of the jumping apparatus in Megalothorax minimus (Neelipleona), Dicyrtomina ornata and Dicyrtomina minuta (Symphypleona). We focus on reconstructing, describing, and understanding the functioning of structures such as basal plates, musculature and furca. The dimensions of the jumping apparatus in Dicyrtomina and Megalothorax differ significantly from those in elongated springtails. A hypothesis of functional coherence between taxa, based on muscle connections and basal plates, is postulated. High-speed video recordings provide information on: 1) furca release timing and function during jumping and self-righting; 2) performance properties of manubrium, dens and mucro in interaction with the ground and in take-off; 3) possible pre-release furca moves. The study underscores the need for further research employing a variety of visualization methods in order to explore additional aspects such as retinaculum unlatching and furca flexion/extension muscles.

Intrahepatic and anterior course of the inferior vena cava: CT image and 3D reconstruction of a rare anatomical variation

The widespread use of computed tomography (CT) for diagnosing and screening abdominal conditions often reveals rare, asymptomatic anomalies. There is a wide range of documented congenital variations in the anatomy of the inferior vena cava (IVC) and hepatic veins. In this report, we detail an exceptionally unusual variant of the IVC that follows a frontward and intraliver course, terminating at the anterior section of the right atrium. To gain a deeper insight into this anomaly, we employed 3D reconstruction techniques using the software Slicer and Blender.

Optical Sensor System for 3D Jones Matrix Reconstruction of Optical Anisotropy Maps of Self-Assembled Polycrystalline Soft Matter Films

Our work uses a polarization matrix formalism to analyze and algorithmically represent optical anisotropy by open dehydration of blood plasma films. Analytical relations for Jones matrix reconstruction of optical birefringence maps of protein crystal networks of dehydrated biofluid films are found. A technique for 3D step-by-step measurement of the distributions of the elements of the Jones matrix or Jones matrix images (JMI) of the optically birefringent structure of blood plasma films (BPF) has been created. Correlation between JMI maps and corresponding birefringence images of dehydrated BPF and saliva films (SF) obtained from donors and prostate cancer patients was determined. Within the framework of statistical analysis of layer-by-layer optical birefringence maps, the parameters most sensitive to pathological changes in the structure of dehydrated films were found to be the central statistical moments of the 1st to 4th orders. We physically substantiated and experimentally determined the sensitivity of the method of 3D polarization scanning technique of BPF and SF preparations in the diagnosis of endometriosis of uterine tissue.

Hash Encoding and Brightness Correction in 3D Industrial and Environmental Reconstruction of Tidal Flat Neural Radiation

We present an innovative approach to mitigating brightness variations in the unmanned aerial vehicle (UAV)-based 3D reconstruction of tidal flat environments, emphasizing industrial applications. Our work focuses on enhancing the accuracy and efficiency of neural radiance fields (NeRF) for 3D scene synthesis. We introduce a novel luminance correction technique to address challenging illumination conditions, employing a convolutional neural network (CNN) for image enhancement in cases of overexposure and underexposure. Additionally, we propose a hash encoding method to optimize the spatial position encoding efficiency of NeRF. The efficacy of our method is validated using diverse datasets, including a custom tidal flat dataset and the Mip-NeRF 360 dataset, demonstrating superior performance across various lighting scenarios.

Validating a Novel 2D to 3D Knee Reconstruction Method on Preoperative Total Knee Arthroplasty Patient Anatomies

BACKGROUND

As advanced technology continues to evolve, incorporating robotics into surgical procedures has become imperative for precision and accuracy in preoperative planning. Nevertheless, the integration of three-dimensional (3D) imaging into these processes presents both financial considerations and potential patient safety concerns. This study aims to assess the accuracy of a novel 2D-to-3D knee reconstruction solution, RSIP XPlan.ai™ (RSIP Vision, Jerusalem, Israel), on preoperative total knee arthroplasty (TKA) patient anatomies.

METHODS

Accuracy was calculated by measuring the Root Mean Square Error (RMSE) between X-ray-based 3D bone models generated by the algorithm and corresponding CT bone segmentations (distances of each mesh vertex to the closest vertex in the second mesh). The RMSE was computed globally for each bone, locally for eight clinically relevant bony landmark regions, and along simulated bone cut contours. In addition, the accuracies of three anatomical axes were assessed by comparing angular deviations to inter- and intra-observer baseline values.

RESULTS

The global RMSE was 0.93 ± 0.25 mm for the femur and 0.88 ± 0.14 mm for the tibia. Local RMSE values for bony landmark regions were 0.51 ± 0.33 mm for the five femoral landmarks and 0.47 ± 0.17 mm for the three tibial landmarks. The RMSE along simulated cut contours was 0.75 ± 0.35 mm for the distal femur cut and 0.63 ± 0.27 mm for the proximal tibial cut. Anatomical axial average angular deviations were 1.89° for the trans epicondylar axis (with an inter- and intra-observer baseline of 1.43°), 1.78° for the posterior condylar axis (with a baseline of 1.71°), and 2.82° (with a baseline of 2.56°) for the medial-lateral transverse axis.

CONCLUSIONS

The study findings demonstrate promising results regarding the accuracy of XPlan.ai™ in reconstructing 3D bone models from plain-film X-rays. The observed accuracy on real-world TKA patient anatomies in anatomically relevant regions, including bony landmarks, cut contours, and axes, suggests the potential utility of this method in various clinical scenarios. Further validation studies on larger cohorts are warranted to fully assess the reliability and generalizability of our results. Nonetheless, our findings lay the groundwork for potential advancements in future robotic arthroplasty technologies, with XPlan.ai™ offering a promising alternative to conventional CT scans in certain clinical contexts.

Study on the use of 3D printed guides in the individualized reconstruction of the anterior cruciate ligament

OBJECTIVE

Evaluation of the accuracy and effectiveness of 3D printed guides to assist femoral tunnel preparation in individualised reconstruction of the anterior cruciate ligament.

METHODS

Sixty patients who attended the Affiliated Hospital of Binzhou Medical College for autologous hamstring single bundle reconstruction of the anterior cruciate ligament from October 2018 to October 2020 were selected and randomly divided into two groups, including 31 cases in the 3D printing group (14 males and 17 females, mean age 41.94 ± 10.15 years) and 29 cases in the control group (13 males and 16 females, mean age 37.76 ± 10.34 years). Patients in both groups were assessed for intraoperative femoral tunnel accuracy, the number of intraoperative positioning and the time taken to prepare the femoral tunnel, the length of the anteromedial approach incision, the pre-planned bone tunnel length and intraoperative bone tunnel length in the 3D printed group, IKDC score and Lysholm score preoperatively and at 3, 6 and 12 months postoperatively, the Lachman、pivot-shift test preoperatively and at 6 months postoperatively, gait analysis to assess internal and external rotation in flexion of the knee at 12 months postoperatively and postoperative complications in both groups.

RESULTS

There was no statistical difference in functional knee scores and anteromedial approach incision length between the 3D printed and control groups (p > 0.05), while there was a statistical difference in the accuracy of tunnel positioning, the time taken to prepare the femoral bone tunnel and the degree of external rotation of the knee in flexion between the two groups (p < 0.05). There was no statistical difference between the preoperative planning of the bone tunnel length and the intraoperative bone tunnel length (p > 0.05).

COMPLICATIONS

One case in the 3D printing group developed intermuscular vein thrombosis in the affected lower limb after surgery, which disappeared after treatment, while three cases in the control group developed intermuscular vein thrombosis in the affected lower limb. No complications such as bone tunnel rupture, deep vein thrombosis in the lower limb and infection occurred in either group.

CONCLUSION

3D printed guides assisted with individualized ACL reconstruction may improve the accuracy of femoral tunnel positioning, which is safe and effective, while reducing the operative time and the number of intraoperative positioning, without increasing the length of incision, and may obtain higher functional scores and rotational stability of the knee joint, which is in line with the concept of individualized ACL reconstruction.

Projection-Angle-Sensor-Assisted X-ray Computed Tomography for Cylindrical Lithium-Ion Batteries

X-ray computed tomography (XCT) has become a powerful technique for studying lithium-ion batteries, allowing non-destructive 3D imaging across multiple spatial scales. Image quality is particularly important for observing the internal structure of lithium-ion batteries. During multiple rotations, the existence of cumulative errors and random errors in the rotary table leads to errors in the projection angle, affecting the imaging quality of XCT. The accuracy of the projection angle is an important factor that directly affects imaging. However, the impact of the projection angle on XCT reconstruction imaging is difficult to quantify. Therefore, the required precision of the projection angle sensor cannot be determined explicitly. In this research, we selected a common 18650 cylindrical lithium-ion battery for experiments. By setting up an XCT scanning platform and installing an angle sensor to calibrate the projection angle, we proceeded with image reconstruction after introducing various angle errors. When comparing the results, we found that projection angle errors lead to the appearance of noise and many stripe artifacts in the image. This is particularly noticeable in the form of many irregular artifacts in the image background. The overall variation and residual projection error in detection indicators can effectively reflect the trend in image quality. This research analyzed the impact of projection angle errors on imaging and improved the quality of XCT imaging by installing angle sensors on a rotary table.

Volumetric Imitation Generative Adversarial Networks for Anatomical Human Body Modeling

Volumetric representation is a technique used to express 3D objects in various fields, such as medical applications. On the other hand, tomography images for reconstructing volumetric data have limited utilization because they contain personal information. Existing GAN-based medical image generation techniques can produce virtual tomographic images for volume reconstruction while preserving the patient's privacy. Nevertheless, these images often do not consider vertical correlations between the adjacent slices, leading to erroneous results in 3D reconstruction. Furthermore, while volume generation techniques have been introduced, they often focus on surface modeling, making it challenging to represent the internal anatomical features accurately. This paper proposes volumetric imitation GAN (VI-GAN), which imitates a human anatomical model to generate volumetric data. The primary goal of this model is to capture the attributes and 3D structure, including the external shape, internal slices, and the relationship between the vertical slices of the human anatomical model. The proposed network consists of a generator for feature extraction and up-sampling based on a 3D U-Net and ResNet structure and a 3D-convolution-based LFFB (local feature fusion block). In addition, a discriminator utilizes 3D convolution to evaluate the authenticity of the generated volume compared to the ground truth. VI-GAN also devises reconstruction loss, including feature and similarity losses, to converge the generated volumetric data into a human anatomical model. In this experiment, the CT data of 234 people were used to assess the reliability of the results. When using volume evaluation metrics to measure similarity, VI-GAN generated a volume that realistically represented the human anatomical model compared to existing volume generation methods.

Software that combines deep learning, 3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging

BACKGROUND

Ultrasound is one of the non-invasive techniques that are used in clinical diagnostics of carotid artery disease.

OBJECTIVE

This paper presents software methodology that can be used in combination with this imaging technique to provide additional information about the state of patient-specific artery.

METHODS

Overall three modules are combined within the proposed methodology. A clinical dataset is used within the deep learning module to extract the contours of the carotid artery. This data is then used within the second module to perform the three-dimensional reconstruction of the geometry of the carotid bifurcation and ultimately this geometry is used within the third module, where the hemodynamic analysis is performed. The obtained distributions of hemodynamic quantities enable a more detailed analysis of the blood flow and state of the arterial wall and could be useful to predict further progress of present abnormalities in the carotid bifurcation.

RESULTS

The performance of the deep learning module was demonstrated through the high values of relevant common classification metric parameters. Also, the accuracy of the proposed methodology was shown through the validation of results for the reconstructed parameters against the clinically measured values.

CONCLUSION

The presented methodology could be used in combination with standard clinical ultrasound examination to quickly provide additional quantitative and qualitative information about the state of the patient's carotid bifurcation and thus ensure a treatment that is more adapted to the specific patient.

3D reconstruction of bone CT scan images based on deformable convex hull

Three-dimensional (3D) reconstruction of computed tomography (CT) and magnetic resonance imaging (MRI) images is an important diagnostic method, which is helpful for doctors to clearly recognize the 3D shape of the lesion and make the surgical plan. In the study of medical image reconstruction, most researchers use surface rendering or volume rendering method to construct 3D models from image sequences. The watertightness of the algorithm-reconstructed surface will be affected by the segmentation precision or the thickness of the CT layer. The articular surfaces at femoral ends are often used in biomechanical simulation experiments. The model may not conform to its original shape due to the manual repair of non-watertight surfaces. To solve this problem, a 3D reconstruction method of leg bones based on deep learning is proposed in this paper. By deforming the convex hull of the target, comparing with state-of-the-art methods, our method can stably generate a watertight model with higher reconstruction accuracy. In the situation of target transition structures getting fuzzy and the layer spacing increasing, the proposed method can maintain better reconstruction performance and appear higher robustness. Also, the chamfer loss is optimized based on the rotational shape of the leg bones, and the weight of the loss function can be assigned according to the geometric characteristics of the target. Experiment results show that the optimization method improves the accuracy of the model. Furthermore, our research provides a reference for the application of deep learning in medical image reconstruction.

Artificial intelligence-based orthopaedic perpetual design

Background and aims

Integrating Artificial Intelligence (AI) methodologies in orthopaedic surgeries is becoming increasingly important as it optimises implant designs and treatment procedures. This research article introduces an innovative approach using an AI-driven algorithm, focusing on the humerus bone anatomy. The primary focus of this work is to determine implant dimensions tailored to individual patients.

Methodology

We have utilised Python's DICOM library, which extracts rich information from medical images obtained through CT and MRI scans. The algorithm generates precise three-dimensional reconstructions of the bone, enabling a comprehensive understanding of its morphology.

Results

Using algorithms that reconstructed 3D bone models to propose optimal implant geometries that adhere to patients' unique anatomical intricacies and cater to their functional requirements. Integrating AI techniques promotes enhanced implant designs that facilitate enhanced integration with the host bone, promoting improved patient outcomes.

Conclusion

A notable breakthrough in this research is the ability of the algorithm to predict implant physical dimensions based on CT and MRI data. The algorithm can infer implant specifications that align with patient-specific bone characteristics by training the AI model on a diverse dataset. This approach could revolutionise orthopaedic surgery, reducing patient waiting times and the duration of medical interventions.

Using high-throughput phenotype platform MVS-Pheno to reconstruct the 3D morphological structure of wheat

It is of great significance to study the plant morphological structure for improving crop yield and achieving efficient use of resources. Three dimensional (3D) information can more accurately describe the morphological and structural characteristics of crop plants. Automatic acquisition of 3D information is one of the key steps in plant morphological structure research. Taking wheat as the research object, we propose a point cloud data-driven 3D reconstruction method that achieves 3D structure reconstruction and plant morphology parameterization at the phytomer scale. Specifically, we use the MVS-Pheno platform to reconstruct the point cloud of wheat plants and segment organs through the deep learning algorithm. On this basis, we automatically reconstructed the 3D structure of leaves and tillers and extracted the morphological parameters of wheat. The results show that the semantic segmentation accuracy of organs is 95.2%, and the instance segmentation accuracy AP50 is 0.665. The R2 values for extracted leaf length, leaf width, leaf attachment height, stem leaf angle, tiller length, and spike length were 0.97, 0.80, 1.00, 0.95, 0.99, and 0.95, respectively. This method can significantly improve the accuracy and efficiency of 3D morphological analysis of wheat plants, providing strong technical support for research in fields such as agricultural production optimization and genetic breeding.

The fertility tracks of pollen tube in the ovary of Solanum nigrum by three-dimensional reconstruction

In this paper, we present an enhanced method for automatically capturing a large number of consecutive paraffin sections using a microscope. Leveraging these microstructural images, we employed three-dimensional visualisation and reconstruction techniques to investigate the dispersal growth process of pollen tube bundles upon entering the ovary of Solanum nigrum. Additionally, we explored their behaviour within different ovules and examined the relationship between the germination rate of seeds and the fertilisation process. Our findings reveal that despite the abundance of Solanum nigrum seeds, only a fraction of them is capable of successful germination. The germination rate of seeds is closely related to whether fertilisation of the ovules and pollen tubes is completed. Due to the limited number of pollen tubes entering the ovary, only a portion of the ovules can be fertilised. The proportion of fertilised ovules positively correlates with the germination rate of the seeds. Through three-dimensional reconstruction, we observed a phenomenon of proximity during the pollination process, wherein ovules closer to the pollen tube bundles are more likely to be fertilised. Furthermore, fertilised ovules exhibited significant changes in morphology and embryo sac structure. The number of fertilised ovules directly impacts the germination rate of wild Solanum nigrum seeds. Although all Solanum nigrum ovules have the potential to develop into seeds, most seeds originating from unfertilised ovules are unable to germinate normally, resulting in an incomplete germination rate of seeds and preventing it from reaching 100%.

Optimizing coronary artery opacification and 3D reconstruction from human cadaver hearts in anatomy research

OBJECTIVE

This study seeks to identify the ideal dilution rate of a radiopaque product to optimize the visualization of coronary arteries and their branches within human cadaver hearts. The process involves obtaining images in the anatomy laboratory and subsequently constructing a three-dimensional model.

MATERIALS AND METHODS

We utilized 30 human hearts fixed in 10 % formalin (9 females and 21 males) with a mean age of 79 ± 5 years. The initial experiment, involving the first four hearts (referred to as "group 1"), encountered difficulties in opacifying coronary arteries. In this phase, a probabilistic injection of 20 % Visipaque and 80 % latex, with coronary sinus ostium closure, was performed. The optimal mixture ratio was then determined as 33 % Visipaque and 66 % latex. Recognizing the need for on-site injection at the CT Scan table, this protocol was applied to the subsequent 11 hearts in "group 2." Closure of the coronary sinus was deemed unnecessary. The final 15 hearts, constituting "group 3," revealed that the injection should be gradual, maintaining controlled pressure between 120 and 150 mm Hg. Post-injection, hearts were scanned with the injected coronary arteries using an Optima 660 CT scanner. Two-dimensional images were acquired with parameters set at 64 × 0.625 mm, 100 kV, 300-400 mA, and a rotation of 0.5 s. Subsequently, 3D reconstruction was conducted using Advantage Workstation 4.7 (GE Healthcare) and volume rendering with Volume Viewer software, version 15.

RESULTS

Significant differences in the percentage of opacified coronaries were observed among the three groups (p < 0.005). This variation underscores the learning curve and comprehension required before establishing a reliable method. Group 1 (N = 4) demonstrated minimal opacification, group 2 (N = 11) displayed partial opacification, while group 3 (N = 15) achieved 100 % opacification of coronary arteries.

CONCLUSION

The successive experiments culminated in the development of a protocol for CT imaging, enabling accurate three-dimensional reconstruction of the normal anatomy of the main and secondary coronary arteries. Our work is grounded in a series of progressively refined and successful experiments.

Case Report: A myxoma with a far reach

A 73-year-old woman presented to the emergency department with a syncopal episode and a history of dizzy spells. A transthoracic echocardiogram demonstrated a large left atrial mass extending into the right upper pulmonary veins. Subsequently, cardiac magnetic resonance imaging and coronary computed tomography angiography with three-dimensional reconstruction and printing of the heart and mass were performed, which demonstrated a high index of suspicion for an atypical left atrial myxoma. The mass was excised robotically, and the pathology report confirmed a diagnosis of myxoma.

Distinct Alterations in Dendritic Spine Morphology in the Absence of β-Neurexins

Dendritic spines are essential for synaptic function because they constitute the postsynaptic compartment of the neurons that receives the most excitatory input. The extracellularly shorter variant of the presynaptic cell adhesion molecules neurexins, β-neurexin, has been implicated in various aspects of synaptic function, including neurotransmitter release. However, its role in developing or stabilizing dendritic spines as fundamental computational units of excitatory synapses has remained unclear. Here, we show through morphological analysis that the deletion of β-neurexins in hippocampal neurons in vitro and in hippocampal tissue in vivo affects presynaptic dense-core vesicles, as hypothesized earlier, and, unexpectedly, alters the postsynaptic spine structure. Specifically, we observed that the absence of β-neurexins led to an increase in filopodial-like protrusions in vitro and more mature mushroom-type spines in the CA1 region of adult knockout mice. In addition, the deletion of β-neurexins caused alterations in the spine head dimension and an increase in spines with perforations of their postsynaptic density but no changes in the overall number of spines or synapses. Our results indicate that presynaptic β-neurexins play a role across the synaptic cleft, possibly by aligning with postsynaptic binding partners and glutamate receptors via transsynaptic columns.

Combined Filtering Method for Offshore Oil and Gas Platform Point Cloud Data Based on KNN_PCF and Hy_WHF and Its Application in 3D Reconstruction

With the increasing scale of deep-sea oil exploration and drilling platforms, the assessment, maintenance, and optimization of marine structures have become crucial. Traditional detection and manual measurement methods are inadequate for meeting these demands, but three-dimensional laser scanning technology offers a promising solution. However, the complexity of the marine environment, including waves and wind, often leads to problematic point cloud data characterized by noise points and redundancy. To address this challenge, this paper proposes a method that combines K-Nearest-Neighborhood filtering with a hyperbolic function-based weighted hybrid filtering. The experimental results demonstrate the exceptional performance of the algorithm in processing point cloud data from offshore oil and gas platforms. The method improves noise point filtering efficiency by approximately 11% and decreases the total error by 0.6 percentage points compared to existing technologies. Not only does this method accurately process anomalies in high-density areas-it also removes noise while preserving important details. Furthermore, the research method presented in this paper is particularly suited for processing large point cloud data in complex marine environments. It enhances data accuracy and optimizes the three-dimensional reconstruction of offshore oil and gas platforms, providing reliable dimensional information for land-based prefabrication of these platforms.