Segmentation of Brain MRI Using U-Net: Innovations in Medical Image Processing

Abstract

Abstract: Medical image segmentation is crucial for finding significant areas or characteristics within images, exclusively in the field of medical identification. Its importance has grown in recent years, with deep learning-based segmentation emerging as an operative tool for image exploration. The segmentation of brain images, which is required for detecting and treating many brain illnesses, is difficult. This effort emphasises U-Net, a deep learning design developed exclusively for image segmentation tasks in brain MRI research. U-Net has demonstrated considerable potential for overcoming these obstacles and has been successfully used in the segmentation of several brain areas, including the cerebral cortex and subcortical regions. In addition to U-Net's use in brain MRI segmentation, we examine the most recent breakthroughs in deep learning algorithms for medical image segmentation.

Keywords: Brain tumors segmentation, U-Net, Residual connections, MRI segmentation, Deep learning