Auto-Segmentation for Radiation Oncology: State of the Art (Series in Medical Physics and Biomedical Engineering) PDF
Preview Auto-Segmentation for Radiation Oncology: State of the Art (Series in Medical Physics and Biomedical Engineering)
Auto-Segmentation for Radiation Oncology Series in Medical Physics and Biomedical Engineering Series Editors Kwan-Hoong Ng, E. Russell Ritenour, and Slavik Tabakov Recent books in the series: Introduction to Megavoltage X-Ray Dose Computation Algorithms Jerry Battista Problems and Solutions in Medical Physics Nuclear Medicine Physics Kwan Hoong Ng, Chai Hong Yeong, Alan Christopher Perkins The Physics of CT Dosimetry CTDI and Beyond Robert L. Dixon Advanced Radiation Protection Dosimetry Shaheen Dewji, Nolan E. Hertel On-Treatment Verifcation Imaging A Study Guide for IGRT Mike Kirby, Kerrie-Anne Calder Modelling Radiotherapy Side Effects Practical Applications for Planning Optimisation Tiziana Rancati, Claudio Fiorino Proton Therapy Physics, Second Edition Harald Paganetti (Ed) e-Learning in Medical Physics and Engineering Building Educational Modules with Moodle Vassilka Tabakova Diagnostic Radiology Physics with MATLAB® A Problem-Solving Approach Johan Helmenkamp, Robert Bujila, Gavin Poludniowski (Eds) Auto-Segmentation for Radiation Oncology State of the Art Jinzhong Yang, Gregory C. Sharp, and Mark J. Gooding For more information about this series, please visit: https :/ /ww w .rout ledge . com/ Seri es -in -Medi cal -P hysic s -and -Biom edica l -Eng ineer ing /b ook -s eries /CHME PHBIO ENG About the Series The Series in Medical Physics and Biomedical Engineering describes the applications of physical sciences, engineering, and mathematics in medicine and clinical research. The series seeks (but is not restricted to) publications in the following topics: • Artifcial organs • Patient monitoring • Assistive technology • Physiological measurement • Bioinformatics • Prosthetics • Bioinstrumentation • Radiation protection, health physics, and • Biomaterials dosimetry • Biomechanics • Regulatory issues • Biomedical engineering • Rehabilitation engineering • Clinical engineering • Sports medicine • Imaging • Systems physiology • Implants • Telemedicine • Medical computing and mathematics • Tissue engineering • Medical/surgical devices • Treatment The Series in Medical Physics and Biomedical Engineering is an international series that meets the need for up-to-date texts in this rapidly developing feld. Books in the series range in level from introductory graduate textbooks and practical handbooks to more advanced expositions of current research. The Series in Medical Physics and Biomedical Engineering is the offcial book series of the International Organization for Medical Physics. THE INTERNATIONAL ORGANIZATION FOR MEDICAL PHYSICS The International Organization for Medical Physics (IOMP) represents over 18,000 medical physi- cists worldwide and has a membership of 80 national and 6 regional organizations, together with a number of corporate members. Individual medical physicists of all national member organisations are also automatically members. The mission of IOMP is to advance medical physics practice worldwide by disseminating scien- tifc and technical information, fostering the educational and professional development of medical physics and promoting the highest quality medical physics services for patients. A World Congress on Medical Physics and Biomedical Engineering is held every three years in cooperation with International Federation for Medical and Biological Engineering (IFMBE) and International Union for Physics and Engineering Sciences in Medicine (IUPESM). A region- ally based international conference, the International Congress of Medical Physics (ICMP) is held between world congresses. IOMP also sponsors international conferences, workshops and courses. The IOMP has several programmes to assist medical physicists in developing countries. The joint IOMP Library Programme supports 75 active libraries in 43 developing countries, and the Used Equipment Programme coordinates equipment donations. The Travel Assistance Programme provides a limited number of grants to enable physicists to attend the world congresses. IOMP co-sponsors the Journal of Applied Clinical Medical Physics. The IOMP publishes, twice a year, an electronic bulletin, Medical Physics World. IOMP also publishes e-Zine, an electronic news letter about six times a year. IOMP has an agreement with Taylor & Francis for the publication of the Medical Physics and Biomedical Engineering series of textbooks. IOMP members receive a discount. IOMP collaborates with international organizations, such as the World Health Organisations (WHO), the International Atomic Energy Agency (IAEA) and other international professional bodies such as the International Radiation Protection Association (IRPA) and the International Commission on Radiological Protection (ICRP), to promote the development of medical physics and the safe use of radiation and medical devices. Guidance on education, training and professional development of medical physicists is issued by IOMP, which is collaborating with other professional organizations in development of a professional certifcation system for medical physicists that can be implemented on a global basis. The IOMP website (www .iomp .org) contains information on all the activities of the IOMP, policy statements 1 and 2 and the ‘IOMP: Review and Way Forward’ which outlines all the activities of IOMP and plans for the future. Auto-Segmentation for Radiation Oncology State of the Art Edited by Jinzhong Yang, Gregory C. Sharp, and Mark J. Gooding First edition published [2021] by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742 and by CRC Press 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN © 2021 Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, LLC Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume respon- sibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microflming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www. copyright .com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. For works that are not available on CCC please contact mpkbookspermissions @tandf .co .uk Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identifcation and explanation without intent to infringe. ISBN: 978-0-367-33600-4 (hbk) ISBN: 978-0-367-76122-6 (pbk) ISBN: 978-0-429-32378-2 (ebk) Typeset in Times by Deanta Global Publishing Services, Chennai, India Contents Foreword I .........................................................................................................................................ix Foreword II .......................................................................................................................................xi Editors ............................................................................................................................................ xiii Contributors .....................................................................................................................................xv Chapter 1 Introduction to Auto-Segmentation in Radiation Oncology ........................................1 Jinzhong Yang, Gregory C. Sharp, and Mark J. Gooding PART I Multi-Atlas for Auto-Segmentation Chapter 2 Introduction to Multi-Atlas Auto-Segmentation ........................................................ 13 Gregory C. Sharp Chapter 3 Evaluation of Atlas Selection: How Close Are We to Optimal Selection? ................ 19 Mark J. Gooding Chapter 4 Deformable Registration Choices for Multi-Atlas Segmentation .............................. 39 Keyur Shah, James Shackleford, Nagarajan Kandasamy, and Gregory C. Sharp Chapter 5 Evaluation of a Multi-Atlas Segmentation System .....................................................49 Raymond Fang, Laurence Court, and Jinzhong Yang PART II Deep Learning for Auto-Segmentation Chapter 6 Introduction to Deep Learning-Based Auto-Contouring for Radiotherapy ............... 71 Mark J. Gooding Chapter 7 Deep Learning Architecture Design for Multi-Organ Segmentation ........................81 Yang Lei, Yabo Fu, Tonghe Wang, Richard L.J. Qiu, Walter J. Curran, Tian Liu, and Xiaofeng Yang Chapter 8 Comparison of 2D and 3D U-Nets for Organ Segmentation ................................... 113 Dongdong Gu and Zhong Xue Chapter 9 Organ-Specifc Segmentation Versus Multi-Class Segmentation Using U-Net ......125 Xue Feng and Quan Chen vii viii Contents Chapter 10 Effect of Loss Functions in Deep Learning-Based Segmentation ...........................133 Evan Porter, David Solis, Payton Bruckmeier, Zaid A. Siddiqui, Leonid Zamdborg, and Thomas Guerrero Chapter 11 Data Augmentation for Training Deep Neural Networks ....................................... 151 Zhao Peng, Jieping Zhou, Xi Fang, Pingkun Yan, Hongming Shan, Ge Wang, X. George Xu, and Xi Pei Chapter 12 Identifying Possible Scenarios Where a Deep Learning Auto-Segmentation Model Could Fail...................................................................................................... 165 Carlos E. Cardenas PART III Clinical Implementation Concerns Chapter 13 Clinical Commissioning Guidelines ........................................................................ 189 Harini Veeraraghavan Chapter 14 Data Curation Challenges for Artifcial Intelligence ............................................... 201 Ken Chang, Mishka Gidwani, Jay B. Patel, Matthew D. Li, and Jayashree Kalpathy-Cramer Chapter 15 On the Evaluation of Auto-Contouring in Radiotherapy ......................................... 217 Mark J. Gooding Index .............................................................................................................................................. 253 Foreword I Auto-segmentation plays an important everyday role in radiotherapy clinics. It is an essential pre- requisite step for complex treatment process that aims to identify the gross tumor volume and sur- rounding organs at risk in order to maximize tumor control while minimizing normal tissue toxicity, which is the holy grail of radiotherapy. With the ever-increasing sophistication of treatment plan- ning procedures and improved delivery systems, accurate contouring becomes a major limitation to an effcient and lean radiotherapy clinic. The process of segmentation has historically been done manually, which makes it not only a laborious and time-consuming task but also prone to errors that may affect the planning quality as well as the patient’s treatment outcomes. Auto-segmentation promises to alleviate this problem; however, its application in the clinic has been slow to meet its demands. Recent years have witnessed the development of more accurate auto-segmentation tools using advanced machine and deep learning techniques that aim at transforming how these tools can be applied reliably in the clinic, but with key questions about their nature and proper implementa- tion remaining open. These questions are thoughtfully answered by the new textbook by Gooding, Sharp, and Yang. This delightful textbook Auto-Segmentation for Radiation Oncology: State of the Art takes the interested reader on a three-part journey from traditional multi-atlas auto-segmentation techniques to more modern deep learning approaches and their implementation in the clinic. In Part I, atlas segmentation methods are discussed: their selection process, combination with deformable regis- tration, and eventually their evaluation. In Part II, deep learning auto-segmentation is presented, starting from architectural designs, comparisons of 2D and 3D approaches with the common U-net architecture, organ-specifc versus multi-class segmentation, effect of loss function and augmenta- tion, ending with pitfalls, in each case using publicly available challenge datasets as examples. Part III addresses practical issues related to clinical commissioning and challenges from data curation to evaluation. This is a must-have textbook for anyone starting on auto-segmentation in radiotherapy or inter- ested in the topic for academic or professional reasons. Finally, I would like to commend the authors on their achievement, bringing a team from industry and academia to address this important topic in radiotherapy and making it feasible for the reader. Issam El-Naqa Chair of Machine Learning H. Lee Mofftt Cancer Center ix
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