0
0
We recommend this book
Overview
- Reference text for machine and deep learning in oncology, medical physics, and radiology
- From theory to practice with examples
- Provides a complete overview of the role of machine learning in radiation oncology and medical physics
About this book
This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members ofapplied machine learning communities.
Machine and Deep Learning in Oncology, Medical Physics and Radiology (Naqa) 2nd edition (2022)
Note : All files uploaded here with reserved copyrights for Medicine-21.com & Dr. Ahmed Hafez
These materials are for personal use and not for commercial use, so avoid copying or transferring these materials to other websites or blogs to avoid being subject to local and international legal accountability.
