Deep Learning for Medical Image Analysis,
Edition 2
Edited by S. Kevin Zhou, Hayit Greenspan and Dinggang Shen

Publication Date: 27 Nov 2023
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. 

Key Features

· Covers common research problems in medical image analysis and their challenges

· Describes the latest deep learning methods and the theories behind approaches for medical image analysis

· Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment

· Includes a Foreword written by Nicholas Ayache

About the author
Edited by S. Kevin Zhou, Principal Key Expert, Medical Image Analysis, Siemens Healthcare Technology Center, Princeton, New Jersey, USA; Hayit Greenspan, Head, Medical Image Processing and Analysis Lab, Biomedical Engineering Department, Faculty of Engineering, Tel-Aviv University, Israel and Dinggang Shen, Professor, Department of Radiology and BRIC, UNC-Chapel Hill, USA
Book details
ISBN: 9780323851244
Page Count: 518
Illustrations : 165 illustrations (135 in full color)
Retail Price : £99.95
Academic and industry researchers and graduate students in medical imaging, computer vision, biomedical engineering, Clinicians, radiographers