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.

• Type: Journal
• Year: 2010
• Where: MICCAI
• Authors: Bjoern H. Menze, Koenraad Van Leemput, Danial Lashkari, Marc-André Weber, Nicholas Ayache, Polina Golland
• Keywords: Medical Imaging, MICCAI 2010, Multivariate Tumor Segmentation, Tumor, Tumor Boundaries