2.5D Multimodal MRI Brain Tumor Segmentation: Beyond 2D Deep Learning Approaches
Abstract This study proposes a 2.5D input framework for brain tumor segmentation in multi-sequence magnetic resonance imaging (MRI), aiming to balance computational efficiency and spatial context compared to conventional 2D approaches. While 2D methods are efficient but limited in capturing inter-slice information, the...