Medical Image Analysis with Deep Learning: Theory and Practice - Intelligent Image Analytics
Book
Hardback
978-1-119-78850-8 (ISBN)
Description
Medical Image Analysis with Deep Learning: Theory and Practice - Intelligent Image Analytics provides a clear understanding of the basics in medical image analytics. It demonstrates how deep learning can be integrated as a core component in different medical image analysis problems, including segmentation, computer-aided detection and diagnosis, visualization, and survival analysis. This book contains exercises as well as sample projects in medical image analysis, using deep learning and complete coding, with corresponding data provided as open access in appropriate websites.
Comprised of 10 chapters, the authors provide examples accompanying each chapter in a detailed manner as well as addressing recent research issues throughout every stage. This book will encompass dedicated chapters discussing many recent and popular deep learning techniques and models, employed for medical image analysis, in order to provide a good background to students on the computational techniques. Providing readers with an in-depth and clear understanding of medical image analysis, this book is an excellent learning tool for graduate students and academic researchers within the field of medical imaging.
Comprised of 10 chapters, the authors provide examples accompanying each chapter in a detailed manner as well as addressing recent research issues throughout every stage. This book will encompass dedicated chapters discussing many recent and popular deep learning techniques and models, employed for medical image analysis, in order to provide a good background to students on the computational techniques. Providing readers with an in-depth and clear understanding of medical image analysis, this book is an excellent learning tool for graduate students and academic researchers within the field of medical imaging.
More details
Person
Subhashis Banerjee is a Visvesvaraya Senior Research Fellow at the Machine Intelligence Unit, Indian Statistical Institute, Kolkata. They gained their M.Tech in Software Engineering From West Bengal University of Technology, Kolkata, India and were selected as the ?Intel Student Ambassador in AI? by the Intel Corporation, USA in 2018.
Sushmita Mitra is an INAE Chair Professor and Fulbright-Nehru Senior Researcher, at the Machine Intelligence Unit (MIU), Indian Statistical Institute, Kolkata. They gained their M. Tech in Computer Science from the University of Calcutta and have published two books ?Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing? and ?Data Mining: Multimedia, Soft Computing, and Bioinformatics? with John Wiley & Sons.
Alejandro Frangi is Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds, Leeds, UK, with joint appointments at the School of Computing and the School of Medicine. He has edited several books, published 7 editorial articles and over 215 journal papers.
Sushmita Mitra is an INAE Chair Professor and Fulbright-Nehru Senior Researcher, at the Machine Intelligence Unit (MIU), Indian Statistical Institute, Kolkata. They gained their M. Tech in Computer Science from the University of Calcutta and have published two books ?Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing? and ?Data Mining: Multimedia, Soft Computing, and Bioinformatics? with John Wiley & Sons.
Alejandro Frangi is Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds, Leeds, UK, with joint appointments at the School of Computing and the School of Medicine. He has edited several books, published 7 editorial articles and over 215 journal papers.