Learning Likelihoods for Labeling (L3): A General Multi-Classifier Segmentation Algorithm

Abstract

PURPOSE To develop an MRI segmentation method for brain tissues, regions, and substructures that yields improved classification accuracy. Current brain segmentation strategies include two complementary strategies. Multi-spectral classification techniques generate excellent segmentations for tissues with clear intensity contrast, but fail to identify… (More)
DOI: 10.1007/978-3-642-23626-6_40

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@article{Weisenfeld2011LearningLF, title={Learning Likelihoods for Labeling (L3): A General Multi-Classifier Segmentation Algorithm}, author={Neil I. Weisenfeld and Simon K. Warfield}, journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention}, year={2011}, volume={14 Pt 3}, pages={322-9} }