Deep Learning Applications In Medical Image Segmentation - Overview, Approaches, And Challenges

Deep Learning Applications in Medical Image Segmentation provides a comprehensive overview of how deep learning techniques are transforming medical image segmentation for diagnosis, research, and treatment. The book covers foundational and advanced models such as FCN, UNet, SegNet, DeepLab, and GANs, while exploring applications in brain tumors, retinal imaging, lung disease detection, and other organ-specific analyses. It also discusses current challenges, recent advancements, and future trends in AI-driven medical image analysis, making it a valuable resource for researchers, biomedical engineers, and medical imaging professionals.