Auto-segmentation for radiation oncology : state of the art /: state of the art. (2021)

• Record Type: Book
• Further Information: Note: Edited by Jinzhong Yang, Gregory C. Sharp, Mark J. Gooding.
• Editors: (Professor of Radiation Physics), Yang, Jinzhong; Sharp, Gregory C; Gooding, Mark J
• Contents: 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-Specific Segmentation Versus Multi-Class Segmentation Using U-Net....... 125 Xue Feng and Quan Chen 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 Artificial 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
• Edition: 1st
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2021
• Extent: 1 online resource, illustrations (black and white, and colour)
• Subjects: 616.9940642; Cancer -- Radiotherapy; Medical physics
• Languages: English
• ISBNs: 9781000376340; 9781000376302; 9780429323782
• Related ISBNs: 9780367336004
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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