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Proceedings Paper

Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model
Author(s): Myungeun Lee; Jong Hyo Kim
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Paper Abstract

Recently, breast MR images have been used in wider clinical area including diagnosis, treatment planning, and treatment response evaluation, which requests quantitative analysis and breast tissue segmentation. Although several methods have been proposed for segmenting MR images, segmenting out breast tissues robustly from surrounding structures in a wide range of anatomical diversity still remains challenging. Therefore, in this paper, we propose a practical and general-purpose approach for segmenting the pectoral muscle boundary based on the structure tensor and deformable model. The segmentation work flow comprises four key steps: preprocessing, detection of the region of interest (ROI) within the breast region, segmenting the pectoral muscle and finally extracting and refining the pectoral muscle boundary. From experimental results we show that the proposed method can segment the pectoral muscle robustly in diverse patient cases. In addition, the proposed method will allow the application of the quantification research for various breast images.

Paper Details

Date Published: 14 February 2012
PDF: 9 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83142P (14 February 2012); doi: 10.1117/12.911181
Show Author Affiliations
Myungeun Lee, Seoul National Univ. (Korea, Republic of)
Jong Hyo Kim, Seoul National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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