Amygdala shape analysis and parametric surface visualization using iterative closest point algorithm and spherical mapping
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概要
- 論文の詳細を見る
The analysis of shape variability of anatomical structures is vital in a number of clinical applications, as abnormalities in shape can be related to the pathogenesis of certain diseases. This study is conducted for the amygdale shape analysis. The goal is three-fold: (1) develop a new framework of internal structure and surface parameter extraction and comparison for 3D shape data; (2) detect amygdale abnormalities in panic disorder using this technique; (3) freely apply various statistical methods and visualization of their results. To align the amygdala shape, Iterative Closest Point (ICP) algorithm is employed. Additionally, a fine-scale spherical mapping is used to generate various 3D shape parameters, including the radius from center to surface, Gaussian and mean curvature, and normal vector of the surface. Various statistical methods such as correlation, t-test, ANOVA, and ANCOVA with clinical parameters can be applied to compare the local shape differences between normal panic disorder patients and healthy comparison subjects. To apply this technique to clinical data, panic disorder patients and healthy volunteers were recruited and scanned by 1.5T MRI. Every amygdala was manually segmented on Tl MRI images and produced into the 3D surface model by Marching Cubes algorithm. The results indicate that group shape differences clearly exist in amygdala between healthy controls and panic disorder patients, which conform to clinical knowledge.
- 社団法人電子情報通信学会の論文
- 2007-01-19
著者
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Renshaw Perry
Brain Imaging Center Mclean Hospital Department Of Psychiatry Harvard Medical School
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YOON Su-Jung
Department of Psychiatry, St. Paul's Hospital, College of Medicine, The Catholic University of Korea
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LYOO In
Department of Psychiatry, Seoul National University College of Medicine
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Kim Namkug
Department of Radiology, Asan Medical Center
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Kim Namkug
Department Of Industrial Engineering Seoul National University
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Lyoo In
Department Of Psychiatry Seoul National University College Of Medicine:interdisciplinary Program In
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Lyoo In
Department Of Psychiatry Clinical Research Institute Seoul National University College Of Medicine A
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Yoon Su-jung
Department Of Psychiatry College Of Medicine Catholic University Of Korea
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Kim Heng
Department of Psychiatry, Seoul National University College of Medicine
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Kang Suk-Ho
Department of Industrial Engineering, Seoul National University
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Dager Stephen
Dept of Radiology, University of Washington School of Medicine
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Kim Heng
Department Of Psychiatry Seoul National University College Of Medicine
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Kang Suk-ho
Department Of Industrial Engineering Seoul National Univ.
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Kang Suk-ho
Department Of Industrial Engineering Seoul National University
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Dager Stephen
Dept Of Radiology University Of Washington School Of Medicine
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