Segmentation of Subcortical Structures in Brain Mri Using Graph-cuts and Subject-specific A-priori Information
نویسندگان
چکیده
We propose a general framework for segmentation of subcortical structures in magnetic resonance brain images based on multi-atlas label propagation and graph cuts. The label maps obtained from multi-atlas segmentation are used to build a subject-specific probabilistic atlas of a structure of interest. From this atlas and an intensity model estimated from the unseen image, a Markov random field-based energy function is defined and via graph cuts. Compared to a previously proposed approach, our method does not rely on manual training of the intensity model and is applied to six subcortical structures. We used this approach to segment the hippocampus on 60 images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and achieved an average overlap (Dice) of 0.86 with a manually delineated reference.
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تاریخ انتشار 2009