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  • Book
    Issam El Naqa, Ruijiang Li, Martin J. Murphy, editors.
    Summary: This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

    Introduction: What is Machine Learning
    Computational Learning Theory
    Overview of Supervised Learning Methods
    Overview of Unsupervised Learning Methods
    Performance Evaluation
    Variety of Applications in Radiation Oncology
    Machine Learning for Quality Assurance: Quality Assurance as a Learning Problem
    Detection of Radiotherapy Errors Using Unsupervised Learning
    Prediction of Radiotherapy Errors Using Supervised Learning
    Machine Learning for Computer-Aided Detection: Detection of Cancer Lesions from Imaging
    Classification of Malignant and Benign Tumours
    Machine Learning for Treatment Planning and Delivery
    Image-guided Radiotherapy with Machine Learning: IMRT Optimization Using Machine Learning
    Treatment Assessment Tools
    Machine Learning for Motion Management: Prediction of Respiratory Motion
    Motion-Correction Using Learning Methods
    Machine Learning Application in 4D-CT
    Machine Learning Application in Dynamic Delivery
    Machine Learning for Outcomes Modeling: Bioinformatics of Treatment Response
    Modelling of Norma Tissue Complication Probabilities (NTCP)
    Modelling of Tumour Control Probability (TCP).
    Digital Access Springer 2015