Deep Learning in Medical Image Analysis: Challenges and Applications (Advances in Experimental Medicine and Biology, 1213)

ISBN 10: 303033127X / ISBN 13: 9783030331276

Edité par Springer, 2020

In. N° de réf. du vendeur ria9783030331276_new

Synopsis :

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.

À propos de l'auteur: 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.

Détails bibliographiques

Titre : Deep Learning in Medical Image Analysis: ...
Éditeur : Springer
Date d'édition : 2020
Reliure : Couverture rigide
Etat : New