A Topographic Representation for Mammogram Segmentation

@incollection{HON03, abstract = {This paper presents a novel segmentation method for delineating regions of interest (ROI\&\#8217;s) in mammograms. The algorithm concurrently detects the breast boundary, the pectoral muscle and dense regions that include candidate masses. The resulting segmentation constitutes an analysis of the global structure of the object in the mammogram. We propose a topographic representation called the iso-level contour map, in which a salient region forms a dense quasi-concentric pattern of contours. The topological and geometrical structure of the image is analysed using an inclusion tree that is a hierarchical representation of the enclosure relationships between contours. The \&\#8220;saliency\&\#8221; of the region is measured topologically as the minimum nesting depth. Experimental results demonstrate that the proposed method achieves a satisfactory performance as a prompt system in the mass detection.}, author = {Hong, Byung-Woo and Brady, Michael}, citeulike-article-id = {3199623}, journal = {Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003}, keywords = {application, attention, medical\_images, roi, saliency}, pages = {730--737}, posted-at = {2008-09-06 14:02:15}, priority = {0}, title = {A Topographic Representation for Mammogram Segmentation}, url = {http://www.springerlink.com/content/n5v72b9chny1590d }, year = {2003} }

TY - CHAP ID - HON03 L3 - citeulike-article-id:3199623 N2 - This paper presents a novel segmentation method for delineating regions of interest (ROI’s) in mammograms. The algorithm concurrently detects the breast boundary, the pectoral muscle and dense regions that include candidate masses. The resulting segmentation constitutes an analysis of the global structure of the object in the mammogram. We propose a topographic representation called the iso-level contour map, in which a salient region forms a dense quasi-concentric pattern of contours. The topological and geometrical structure of the image is analysed using an inclusion tree that is a hierarchical representation of the enclosure relationships between contours. The “saliency” of the region is measured topologically as the minimum nesting depth. Experimental results demonstrate that the proposed method achieves a satisfactory performance as a prompt system in the mass detection. JF - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003 EP - 737 TI - A Topographic Representation for Mammogram Segmentation SP - 730 KW - application KW - attention KW - medical_images KW - roi KW - saliency AU - Hong, Byung-Woo AU - Brady, Michael PY - 2003/// UR - http://www.springerlink.com/content/n5v72b9chny1590d ER -