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CVPR 2011

DOI: 10.1109/cvpr.2011.5995382

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Regression-Based Label Fusion for Multi-Atlas Segmentation

Proceedings article published in 2011 by Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, John Pluta, Murat Altinay, Paul A. Yushkevich ORCID
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This paper is available in a repository.

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Abstract

Automatic segmentation using multi-atlas label fusion has been widely applied in medical image analysis. To simplify the label fusion problem, most methods implicitly make a strong assumption that the segmentation errors produced by different atlases are uncorrelated. We show that violating this assumption significantly reduces the efficiency of multi-atlas segmentation. To address this problem, we propose a regression-based approach for label fusion. Our experiments on segmenting the hippocampus in magnetic resonance images (MRI) show significant improvement over previous label fusion techniques.