A procedure for multimodal brain tumor segmentation

Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique for generating three dimensional (3D) anatomical images of soft tissues in the body. In the brain, MRI can help distinguish healthy tissues and a variety of tumor tissues. The process of splitting a brain image into healthy tissues and tumor tissues is brain tumor segmentation. Brain tumor segmentation is challenging since the shapes and appearances of tumor regions vary in a brain. Interpretable, accurate, and reproducible approaches for brain tumor segmentation are in demand because they are crucial to diagnosis, treatment planning, and follow-ups of brain tumors. A novel three-stage procedure, which consists of preprocessing, processing, and post-processing stages, is proposed in the thesis for brain tumor segmentation. Instead of being analyzed simultaneously, the MR images are preprocessed and processed in a sequence. Then the intermediate results are combined in the postprocessing stage. Experiments have been conducted on the data from the Multimodal Brain Tumor Segmentation Challenge (BraTS 2019). The results demonstrate that the proposed procedure can produce accurate brain tumor segmentations.