Atlas-Based Segmentation of Pathological Brain MR Images

We propose a method for brain atlas deformation in presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed, combining a method derived from optical flow principles and a model of lesion growth (MLG). Results show that the method can be applied to the automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery and radiotherapy.