Deep Learning-Based Medical Image Segmentation for Precise Disease Localization

Abstract

Medical image segmentation plays a crucial role in diagnosing and treating diseases by precisely localizing affected areas. Deep learning techniques have shown remarkable performance in this field, offering unprecedented accuracy and efficiency. This research explores the application of deep learning for medical image segmentation, focusing on precise disease localization. Various deep learning architectures and methodologies are reviewed and evaluated for their effectiveness in segmenting medical images. The study aims to contribute insights into the current state-of-the-art, challenges, and future directions in deep learning- based medical image segmentation for disease localization.