{"product_id":"deep-learning-applications-in-medical-image-segmentation-overview-approaches-and-challenges-1st-edition","title":"Deep Learning Applications in Medical Image Segmentation: Overview, Approaches, and Challenges 1st Edition","description":"\u003cdiv id=\"bookDescription_feature_div\" class=\"celwidget\" data-feature-name=\"bookDescription\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"bookDescription\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-asin=\"0993745598\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"7y9w7h-rgk3d4-2xixgp-6jetc1\" data-cel-widget=\"bookDescription_feature_div\"\u003e\n\u003cdiv data-a-expander-name=\"book_description_expander\" data-a-expander-collapsed-height=\"280\" class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\"\u003e\n\u003cdiv aria-expanded=\"false\" class=\"a-expander-content a-expander-partial-collapse-content\"\u003e\n\u003cp\u003e\u003cspan class=\"a-text-bold\"\u003eApply revolutionary deep learning technology to the fast-growing field of medical image segmentation\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003ePrecise 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.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan class=\"a-text-italic\"\u003eDeep Learning Applications in Medical Image Segmentation\u003c\/span\u003e\u003cspan\u003e 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.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eReaders will also find:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul class=\"a-unordered-list a-vertical\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eAnalysis of deep learning models, including FCN, UNet, SegNet, Dee Lab, and many more\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eDetailed discussion of medical image segmentation divided by area, incorporating all major organs and organ systems\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eRecent deep learning advancements in segmenting brain tumors, retinal vessels, and inner ear structures\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eAnalyzes the effectiveness of deep learning models in segmenting lung fields for respiratory disease diagnosis\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eExplores the application and benefits of Generative Adversarial Networks (GANs) in enhancing medical image segmentation\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eIdentifies and discusses the key challenges faced in medical image segmentation using deep learning techniques\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan\u003eProvides an overview of the latest advancements, applications, and future trends in deep learning for medical image analysis\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cspan class=\"a-text-italic\"\u003eDeep Learning Applications in Medical Image Segmentation\u003c\/span\u003e\u003cspan\u003e is ideal for academics and researchers working with medical image segmentation, as well as professionals in medical imaging, data science, and biomedical engineering.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"celwidget aplus-module module-12 aplus-standard\" data-cel-widget=\"aplus-module-12\" data-csa-c-id=\"e48qwb-36wm3s-vb6e8j-pnxs9b\"\u003e\n\u003cdiv class=\"aplus-module-wrapper apm-spacing apm-floatnone apm-fixed-width\"\u003e\n\u003cdiv class=\"apm-sidemodule aplus-module-content\"\u003e\u003cbr\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"a-section a-spacing-small a-padding-base\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cb\u003eBOOKREAD™ 5-STEP SATISFACTION GUARANTEE\u003c\/b\u003e\u003c\/strong\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003e1. No Risk, 30-Day Money-Back Guarantee. \u003cbr\u003e2. instant download. No surprises or hidden fees.\u003cbr\u003e3. Safe Payments via Credit\/Debit Card or PayPal® \u003cbr\u003e4. McAfee™ and SSL secured shopping cart.\u003cbr\u003e5. lifetime customer support.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cbr\u003e\u003c\/div\u003e","brand":"My Store","offers":[{"title":"PDF","offer_id":56778127704395,"sku":null,"price":29.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1031\/1204\/8971\/files\/81SCr_rkMuL._SL1500.jpg?v=1773316538","url":"https:\/\/bookread.io\/products\/deep-learning-applications-in-medical-image-segmentation-overview-approaches-and-challenges-1st-edition","provider":"bookread","version":"1.0","type":"link"}