Atlas selection strategy using least angle regression in multi-atlas segmentation propagation

International audience; In multi-atlas based segmentation propagation, segmentations from multiple atlases are propagated to the target image and combined to produce the segmentation result. Local weighted voting (LWV) method is a classifier fusion method which combines the propagated atlases weighted by local image similarity. We demonstrate that the segmentation accuracy using LWV improves as the number of atlases increases. Under this context, we show that introducing diversity in addition to image similarity by using least-angle regression (LAR) criteria is a more efficient way to rank and select atlases. The accuracy of multi-atlas segmentation converges faster when the atlases are sel…