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Regression-Based Label Fusion for Multi-Atlas Segmentation.
- Source :
-
Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops [Conf Comput Vis Pattern Recognit Workshops] 2011 Jun 20, pp. 1113-1120. - Publication Year :
- 2011
-
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.
Details
- Language :
- English
- ISSN :
- 2160-7508
- Database :
- MEDLINE
- Journal :
- Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops
- Publication Type :
- Academic Journal
- Accession number :
- 22562785
- Full Text :
- https://doi.org/10.1109/CVPR.2011.5995382