The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform
Amy Yuan - One of the best experts on this subject based on the ideXlab platform.
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TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion
Medical Physics, 2014Co-Authors: Jie Wei, Amy YuanAbstract:Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, Segment, Register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung Segmentation algorithm was designed and 4D lung Segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is
Jie Wei - One of the best experts on this subject based on the ideXlab platform.
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TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion
Medical Physics, 2014Co-Authors: Jie Wei, Amy YuanAbstract:Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, Segment, Register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung Segmentation algorithm was designed and 4D lung Segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is
Yang Xing-zi - One of the best experts on this subject based on the ideXlab platform.
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Design of microprocessor Segment cache loading
Journal of Tsinghua University, 2001Co-Authors: Yang Xing-ziAbstract:In microprocessor protected mode, the Segment Register does not represent the Segment base address as in real mode but becomes a selector which can index a descriptor in the GDT/LDT (Global/Local descriptor table). A descriptor contains a Segment base address, a limit and an attribute. The number of visits to descriptors in memory can be reduced by having every Segment Register set up a corresponding Segment cache to hold a descriptor. This paper firstly analyzes the definitions and data structures for Segment cache loading to design an algorithm for Segment cache looding. The algorithm is then used to propose a kind of cell group architecture to build the PTU (Protection Test Unit) for Segment cache loading. A boolean value is generated from the PTU to control branching of the microprogram for the Segment cache loading algorithms. The RTL VHDL description for the PTU and the microprogram have been synthesized for the algorithm with SYNOPSYS tools to prove the validity of the PTU.
Dennis P. Hanson - One of the best experts on this subject based on the ideXlab platform.
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Biomedical image visualization research using the Visible Human Datasets
Clinical anatomy (New York N.Y.), 2006Co-Authors: Richard A. Robb, Dennis P. HansonAbstract:The practice of medicine and conduct of research in major Segments of the biologic sciences have always relied on visualizations to study the relationship of anatomic structure to biologic function. Traditionally, these visualizations have either been direct, via vivisection and postmortem examination, or have required extensive mental reconstruction. The revolutionary capabilities of 3-D and 4-D medical imaging modalities, together with computer reconstruction and rendering of multidimensional medical and histological volume image data, obviate the need for physical dissection or abstract assembly. The availability of the Visible Human Datasets from the National Library of Medicine, coupled with the development of advanced computer algorithms to accurately and rapidly process, Segment, Register, measure, and display high resolution 3-D images, has provided a rich opportunity to help advance these important new imaging, visualization, and analysis methodologies from scientific theory to clinical practice.
Richard A. Robb - One of the best experts on this subject based on the ideXlab platform.
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Biomedical image visualization research using the Visible Human Datasets
Clinical anatomy (New York N.Y.), 2006Co-Authors: Richard A. Robb, Dennis P. HansonAbstract:The practice of medicine and conduct of research in major Segments of the biologic sciences have always relied on visualizations to study the relationship of anatomic structure to biologic function. Traditionally, these visualizations have either been direct, via vivisection and postmortem examination, or have required extensive mental reconstruction. The revolutionary capabilities of 3-D and 4-D medical imaging modalities, together with computer reconstruction and rendering of multidimensional medical and histological volume image data, obviate the need for physical dissection or abstract assembly. The availability of the Visible Human Datasets from the National Library of Medicine, coupled with the development of advanced computer algorithms to accurately and rapidly process, Segment, Register, measure, and display high resolution 3-D images, has provided a rich opportunity to help advance these important new imaging, visualization, and analysis methodologies from scientific theory to clinical practice.