A generative model for brain tumor segmentation in multi-modal images

Citation:

Bjoern H Menze, Koen Van Leemput, Danial Lashkari, Marc-André Weber, Nicholas Ayache, and Polina Golland. 2010. “A generative model for brain tumor segmentation in multi-modal images.” Med Image Comput Comput Assist Interv, 13, Pt 2, Pp. 151-9.

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.
Last updated on 01/24/2017