A 3D Framework for Brain Tumor Segmentation from Multi-modal MR Images.

Segmentation of brain tumors from multi-modal magnetic resonance (MR) images is a crucial task in medical imaging, with significant clinical implications for the diagnosis and treatment planning of relevant brain disorders. In this paper, we present a 3D framework, that utilizes multi-modal MR images, including T1-weighted, T1ce-weighted, T2-weighted, and FLAIR images, to capture comprehensive information about the tumor for precise and automated brain tumor segmentation. The proposed framework leverages a multi-modal MRI fusion task to facilitate the optimization and training of brain tumor segmentation. Comparative experiments have indicated the effectiveness and superiority of the proposed framework for brain tumor segmentation tasks.