A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation— With Application to Tumor and Stroke

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation— With Application to Tumor and Stroke

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM), to estimate...

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Bibliographic Details
Main Authors: Van Leemput, Koen, Riklin-Raviv, Tammy, Geremia, Ezequiel, Alberts, Esther, Gruber, Philipp, Wegener, Susanne, Weber, Marc-Andre, Szekely, Gabor, Ayache, Nicholas, Menze, Bjoern Holger, Lashkari, Danial, Golland, Polina
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2017
Online Access:http://hdl.handle.net/1721.1/110983
https://orcid.org/0000-0003-2516-731X

Internet

http://hdl.handle.net/1721.1/110983
https://orcid.org/0000-0003-2516-731X

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