Automatic Brain Tumor Segmentation & Tumor Tissue Classification Based on Multiple MR Protocols

Astrid Franz¹, Henriette Tschampa², Andreas Mller², Stefanie Remmele¹, Jochen Keupp¹, Jrgen Gieseke³, Hans Heinz Schild², Petra Mrtz²

We present a nearly automatic segmentation and classification algorithm for human brain tumor tissue working on a combination of magnetic resonance T1 weighted contrast enhanced images and FLAIR images, based on a simple region growing technique. Algorithmic parameters are adapted automatically in the course of growing. The only required user interaction is a mouse click for providing the starting point. The algorithm is robust, i.e. independent of the given starting point within the tumor, and avoids leakage. We validated the algorithm on 20 test cases of human glioblastoma and meningioma. In 85% of the test cases we got satisfactory results.