Leveraging Ensemble Deep Learning for Enhanced Brain Tumor Analysis: Integrating YOLOv8, Mask R-CNN, and U-Net

Brain tumors pose a significant health threat, and accurate detection and segmentation are crucial for treatment. This paper proposes a novel deep learning approach integrating U-Net for precise segmentation and YOLOv8 for efficient tumor detection in MRI scans. U-Net is optimized for accurate delineation, while YOLOv8, enhanced with attention and spatial pooling, facilitates efficient tumor localization. Image enhancement and data augmentation further boost performance. Furthermore, U-Net, an architecture known for its segmentation capabilities, will be explored in conjunction with fine-tuning for brain tumor segmentation This integrated approach is expected to achieve competitive accuracy and efficiency, potentially improving clinical decision-making in brain tumor diagnosis and treatment.