کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
525785 869025 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Graph cut segmentation with a statistical shape model in cardiac MRI
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Graph cut segmentation with a statistical shape model in cardiac MRI
چکیده انگلیسی


• Challenging segmentation of the right ventricle in cardiac MR images.
• Use of a statistical shape model based on a signed distance function in order to constrain the segmentation.
• The shape prior is introduced into a graph cut approach.
• Results are comparable to the state-of-the-art in RV segmentation.

Segmenting the right ventricle (RV) in magnetic resonance (MR) images is required for cardiac function assessment. The segmentation of the RV is a difficult task due to low contrast with surrounding tissues and high shape variability. To overcome these problems, we introduce a segmentation method based on a statistical shape model obtained with a principal component analysis (PCA) on a set of representative shapes of the RV. Shapes are not represented by a set of points, but by distance maps to their contour, relaxing the need for a costly landmark detection and matching process. A shape model is thus obtained by computing a PCA on the shape variations. This prior is registered onto the image via a very simple user interaction and then incorporated into the well-known graph cut framework in order to guide the segmentation. Our semi-automatic segmentation method has been applied on 248 MR images of a publicly available dataset (from MICCAI’12 Right Ventricle Segmentation Challenge). We show that encouraging results can be obtained for this challenging application.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 117, Issue 9, September 2013, Pages 1027–1035
نویسندگان
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