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Overview: Apply revolutionary Deep Learning technology to the fast-growing field of medical image segmentation. Precise medical image segmentation is rapidly becoming one of the most important tools in medical research, diagnosis, and treatment. The potential for Deep Learning, a technology which is already revolutionizing practice across hundreds of subfields, is immense. The prospect of using Deep Learning to address the traditional shortcomings of image segmentation demands close inspection and wide proliferation of relevant knowledge. Deep Learning Applications in Medical Image Segmentation meets this demand with a comprehensive introduction and its growing applications. Covering foundational concepts and its advanced techniques, it offers a one-stop resource for researchers and other readers looking for a detailed understanding of the topic. It is deeply engaged with the main challenges and recent advances in the field of deep-learning-based medical image segmentation. The book also covers cutting-edge topics such as the use of generative adversarial networks (GANs) for image segmentation and collaborative models for cell image segmentation. By including these advanced topics, we aim to provide readers with a forward-looking perspective on the future of medical image segmentation.
Genre: Non-Fiction > Tech & Devices
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