Deep Learning in Medical Image Analysis
Challenges and Applications
Published on 7. February 2020
Book
Hardback
VIII, 181 pages
978-3-030-33127-6 (ISBN)
Description
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.
More details
Product info
Book
Series
Edition
1st ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
College/higher education
Illustrations
114 farbige Abbildungen, 17 s/w Abbildungen
VIII, 181 p. 131 illus., 114 illus. in color.
Dimensions
Height: 25.4 cm
Width: 17.8 cm
Weight
602 gr
ISBN-13
978-3-030-33127-6 (9783030331276)
DOI
10.1007/978-3-030-33128-3
Schweitzer Classification
Other editions
Additional editions
Book
02/2021
Springer
€213.99
Shipment within 7-9 days
E-Book
02/2020
1st Edition
Springer
€213.99
Available for download
Persons
Gobert Lee is a lecturer in Statistical Science and the Director of Studies in Mathematics and Statistics at the College of Science and Engineering, and a research member of the Medical Device Research Institute, Flinders University, Adelaide, Australia. Gobert's research interests include statistical pattern recognition, medical image segmentation, computer-aided-diagnosis systems, breast cancer detection and analysis, multi-organ CT segmentation and human voxel model generation.
Hiroshi Fujita is a Research Professor/Emeritus Professor of Gifu University. He is a member of the Society for Medical Image Information (president), the Research Group on Medical Imaging (adviser), the Japan Society for Medical Image Engineering (director), and some other societies. His research interests include computer-aided diagnosis system, image analysis and processing, and image evaluation in medicine. He has published over 1000 papers in Journals, Proceedings, Book chapters and Scientific Magazines.
Hiroshi Fujita is a Research Professor/Emeritus Professor of Gifu University. He is a member of the Society for Medical Image Information (president), the Research Group on Medical Imaging (adviser), the Japan Society for Medical Image Engineering (director), and some other societies. His research interests include computer-aided diagnosis system, image analysis and processing, and image evaluation in medicine. He has published over 1000 papers in Journals, Proceedings, Book chapters and Scientific Magazines.