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29 March 2007 Segmentation of suspicious lesions in dynamic contrast-enhanced breast MR images
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Dynamic contrast enhanced breast MRI (DCE BMRI) is an emerging tool for breast cancer diagnosis. There is a clear clinical demand for computer-aided diagnosis (CADx) tools to support radiologists in the diagnostic reading process of DCE BMRI studies. A crucial step in a CADx system is the segmentation of tumors, which allows for accurate assessment of the 3D lesion size and morphology. In this paper we propose a semiautomatic segmentation procedure for suspicious breast lesions. The proposed methodology consists of four steps: (1) Robust seed point selection. This interaction mode ensures robustness of the segmentation result against variations in seed-point placement. (2) Automatic intensity threshold estimation in the subtraction image. (3)Connected component analysis based on the estimated threshold. (4) A post-processing step that includes non-enhancing portions of the lesion into the segmented area and removes attached vessels. The proposed methodology was applied to DCE BMRI data acquired at different institutions using different protocols.
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Thomas Bülow, Lina Arbash Meinel, Rafael Wiemker, Ursula Kose, Akiko Shimauchi, and Gillian Newstead M.D. "Segmentation of suspicious lesions in dynamic contrast-enhanced breast MR images", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65140T (29 March 2007);

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