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Deep Learning in Medical Image Analysis

Deep Learning in Medical Image Analysis

Challenges and Applications

by Gobert Lee and Hiroshi Fujita
Paperback
Publication Date: 07/02/2021

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This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
ISBN:
9783030331306
9783030331306
Category:
Medical imaging
Format:
Paperback
Publication Date:
07-02-2021
Publisher:
Springer Nature Switzerland AG
Country of origin:
Switzerland
Pages:
181
Dimensions (mm):
254x178mm
Weight:
0.45kg

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