XAI-MRI: an ensemble dual-modality approach for 3D brain tumor segmentation using magnetic resonance imaging.

ABSTRACT: Brain tumor segmentation from Magnetic Resonance Images (MRI) presents significant challenges due to the complex nature of brain tumor tissues. This complexity poses a significant challenge in distinguishing tumor tissues from healthy tissues, particularly when radiologists rely on manual segmentation. Reliable and accurate segmentation is crucial for effective tumor grading and treatment planning. In this paper, we proposed a novel ensemble dual-modality approach for 3D brain tumor segmentation using MRI. Initially, individual U-Net models are trained and evaluated on single MRI modalities (T1, T2, T1ce, and FLAIR) to establish each modality's performance. Subsequently, we trained U-net models using combinations of the best-performing modalities to exploit the complementary information an

SUBMITTER: Farhan AS 

PROVIDER: S-EPMC11880613 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature