Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation

arXiv:2403.09942v1 Announce Type: cross
Abstract: Glioblastoma is a highly aggressive and malignant brain tumor type that requires early diagnosis and prompt intervention. Due to its heterogeneity in appearance, developing automated detection approaches is challenging. To address this challenge, Artificial Intelligence (AI)-driven approaches in healthcare have generated interest in efficiently diagnosing and evaluating brain tumors. The Brain Tumor Segmentation Challenge (BraTS) is a platform for developing and assessing automated techniques for tumor analysis using high-quality, clinically acquired MRI data. In our …

aggregation arxiv attention brain cs.cv cs.lg eess.iv feature hybrid network segmentation type