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Proceedings Paper

Multi-atlas based segmentation of multiple organs in breast MRI
Author(s): Xi Liang; Suman Sedai; Hongzhi Wang; Sisi Liang; Naveed Hashmi; Patrick Mcneillie; Sharbell Hashoul
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Paper Abstract

Automatic segmentation of the breast, chest wall and heart is an important pre-processing step for automatic lesion detection of breast MR and dynamic contrast-enhanced MR studies. In this paper, we present a fully automatic segmentation procedure of multiple organs in breast MRI images using multi-atlas based methods. Our method starts by reducing the image inhomogeneity using anisotropic fusion method. We then build multiple atlases with labels of breast, chest wall and heart. These atlases are registered to a target image to obtain warped organ labels that are aligned to the target image. Given the warped organ labels, segmentation is performed via label fusion. In this paper, we evaluate various label fusion methods and compare their performance on segmenting multiple anatomical structures in breast MRI.

Paper Details

Date Published: 20 March 2015
PDF: 6 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94133R (20 March 2015); doi: 10.1117/12.2081127
Show Author Affiliations
Xi Liang, IBM Research - Australia (Australia)
Suman Sedai, IBM Research - Australia (Australia)
Hongzhi Wang, IBM Research - Almaden (United States)
Sisi Liang, IBM Research - Australia (Australia)
Naveed Hashmi, IBM Research - Australia (Australia)
Patrick Mcneillie, IBM Research - Almaden (United States)
Sharbell Hashoul, IBM Research - Haifa (Israel)


Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)

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