@inproceedings{b29549de46d741838372a215430460b6,
title = "A generative model for brain tumor segmentation in multi-modal images",
abstract = "We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, reflecting difference in tumor appearance across modalities. We augment a probabilistic atlas of healthy tissue priors with a latent atlas of the lesion and derive the estimation algorithm to extract tumor boundaries and the latent atlas from the image data. We present experiments on 25 glioma patient data sets, demonstrating significant improvement over the traditional multivariate tumor segmentation.",
author = "Menze, {Bjoern H.} and {Van Leemput}, Koen and Danial Lashkari and Weber, {Marc Andr{\'e}} and Nicholas Ayache and Polina Golland",
year = "2010",
doi = "10.1007/978-3-642-15745-5_19",
language = "English",
isbn = "3642157440",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "151--159",
booktitle = "Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings",
edition = "PART 2",
note = "13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 ; Conference date: 20-09-2010 Through 24-09-2010",
}