Multi-modal Brain Tumor Segmentation via Latent Atlases

In this work, a generative approach for patient-specific segmentation of brain tumors across different MR modalities is presented. It is based on the latent atlas approach presented in [7, 8]. The individual segmentation of each scan supports the segmentation of the ensemble by sharing common information. This common information, in the form of a spatial probability map of the tumor location is inferred concurrently with the evolution of the segmentations. The joint segmentation problem is solved via a statistically driven level-set framework. We illustrate the method on an example application of multimodal and longitudinal brain tumor segmentation, reporting promising segmentation results.