Deep Learning for Medical Image Analysis: A Comprehensive Guide

Deep learning is revolutionizing the field of medical image analysis, providing innovative solutions to complex problems. This book offers a comprehensive understanding of neural network and deep learning concepts, demonstrating how these algorithms are applied to medical image detection, segmentation, and registration, as well as computer-aided analysis.

Deep Learning for Medical Image Analysis serves as an excellent learning resource for both academic and industry researchers in medical imaging analysis, and for graduate students studying machine learning and deep learning for computer vision and medical image computing and analysis.

Covering Common Challenges in Medical Image Analysis

This book addresses common research problems in medical image analysis and their challenges, providing insights into the theoretical foundations of deep learning methods. It delves into the application of these algorithms across a broad range of medical imaging areas, including:

• Chest X-ray analysis
• Breast CAD detection
• Lung and chest imaging
• Microscopy and pathology analysis

A Foreword by Nicholas Ayache

The book includes a foreword written by renowned researcher Nicholas Ayache, adding further credibility and insight to the comprehensive guide.

Key Features

Deep Learning for Medical Image Analysis offers:

• A detailed understanding of deep learning methods and their theoretical foundations
• Practical applications of algorithms across various medical imaging domains
• A valuable resource for researchers and students in the field of medical imaging and machine learning

Published by Academic Press, this book is an essential read for anyone looking to explore the intersection of deep learning and medical image analysis.