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Atlas Selection for Atlas-Based Segmentation

By T. Duindam

Abstract

Atlas-based image segmentation is a powerful method of segmenting an image. An atlas in this context consists of an image and its segmentation. Atlas-based segmentation works by registering the atlas-image to a subject image, and propagating the labels from the atlas-segmentation. Atlas selection has proven to be crucial for the segmentation quality. Several methods to select an atlas exist. This work compares the following atlas selection strategies: single atlas, cohort atlas, most similar atlas, average atlas, and multiple atlases. Different methods have different strengths and weaknesses. If multiple atlases are used a decision fusion algorithm is needed to fuse the propagated labels from different registrations. The VOTE and Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm for decision fusion are described here

Topics: Geneeskunde, Atlas-based Segmantation, Image Segmentation, Image Registration, Literature Review
Year: 2010
OAI identifier: oai:dspace.library.uu.nl:1874/42401
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