Deep learning applications in medical image segmentation overview, approaches, and challenges / edited by Sajid Yousuf Bhat, Department of Computer Science, University of Kashmir, Srinagar, India, Aasia Rehman, Department of Computer Science, University of Kashmir, Srinagar, India, Muhammad Abulaish, Department of Computer Science, South Asian University, New Delhi, India.

Other author Bhat, Sajid Yousuf
Other author Rehman, Aasia
Other author Abulaish, Muhammad
Format Electronic
EditionFirst edition.
Publication InfoHoboken, New Jersey : Wiley-IEEE Press, [2026]
Descriptionpages cm
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

Partial contents Introduction to medical image segmentation : overview of modalities, benchmark datasets, data augmentation techniques, and evaluation metrics / Aasia Rehman and Suhail Qadir Mir -- Fundamentals of deep learning models for medical image segmentation / Aasia Rehman and Sajid Yousuf Bhat -- Revealing historical insights : a comprehensive exploration of traditional approaches in medical image segmentation / Mudasir Ashraf and Majid Zaman.
Abstract "This book applies deep learning models to medical image segmentation technologies, focusing on the fundamental concepts, advanced techniques, and recent challenges, looking to the future on how we can solve challenges faced. With recent advancements in imaging technologies, the Editors focus on new trends and directions including imbalanced class distribution, limited annotated data, deployment of segmentation models, and more. Fusions of medical image segmentation are discussed and advanced architectures are explained. This book applies a variety of deep learning techniques to medical fields such as thoracic and abdominal organs, microscopic and dermoscopy images, and addresses the different types of deep learning models like FCN, UNet, Deep Lab, SegNet, and PSP-Net. Suitable for professionals and researchers in the field of image processing, this book will aid readers in their understanding of the technologies"-- Provided by publisher.
General noteIncludes index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2025046673
ISBN9781394245338 cloth
ISBNadobe pdf
ISBNepub

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