Multi-atlas based segmentation of multiple organs in breast MRI

Xi Liang; Suman Sedai; Hongzhi Wang; Sisi Liang; Naveed Hashmi; Patrick Mcneillie; Sharbell Hashoul

doi:10.1117/12.2081127

20 March 2015 Multi-atlas based segmentation of multiple organs in breast MRI

Xi Liang, Suman Sedai, Hongzhi Wang, Sisi Liang, Naveed Hashmi, Patrick Mcneillie, Sharbell Hashoul

Author Affiliations +

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94133R (2015) https://doi.org/10.1117/12.2081127
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

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.

Citation Download Citation

Xi Liang, Suman Sedai, Hongzhi Wang, Sisi Liang, Naveed Hashmi, Patrick Mcneillie, and Sharbell Hashoul "Multi-atlas based segmentation of multiple organs in breast MRI", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94133R (20 March 2015); https://doi.org/10.1117/12.2081127

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