[PDF] Deep Learning For Online Adaptive Radiotherapy - eBooks Review

Deep Learning For Online Adaptive Radiotherapy


Deep Learning For Online Adaptive Radiotherapy
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Deep Learning For Online Adaptive Radiotherapy


Deep Learning For Online Adaptive Radiotherapy
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Author :
language : en
Publisher:
Release Date : 2022

Deep Learning For Online Adaptive Radiotherapy written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.




Machine Learning Based Adaptive Radiotherapy Treatments From Bench Top To Bedside


Machine Learning Based Adaptive Radiotherapy Treatments From Bench Top To Bedside
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Author : Jiahan Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2023-05-12

Machine Learning Based Adaptive Radiotherapy Treatments From Bench Top To Bedside written by Jiahan Zhang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-12 with Medical categories.




Investigation Of Adaptive Radiation Therapy Including Deformable Image Registration Treatment Planning Modification Strategies Machine Learning Deep Learning


Investigation Of Adaptive Radiation Therapy Including Deformable Image Registration Treatment Planning Modification Strategies Machine Learning Deep Learning
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Author : Pawel Siciarz
language : en
Publisher:
Release Date : 2021

Investigation Of Adaptive Radiation Therapy Including Deformable Image Registration Treatment Planning Modification Strategies Machine Learning Deep Learning written by Pawel Siciarz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.


The goal of this research was to propose and evaluate solutions to four important aspects of adaptive radiation therapy in order to make it more reliable, accurate, and efficient in clinical environment. The first study focused on the evaluation of several deformable image registration algorithms. Results demonstrated that the Dense Anatomical Block Matching registration outperformed the other methods making it a very promising alternative to the existing registration methods for challenging CT-to-CBCT registration and its applications for radiation dose calculation, dose mapping and contour propagation in adaptive radiation therapy (ART) of the pelvic region. The second study focused on the quantitative evaluation of eight proposed adaptive radiation therapy approaches for prostate cancer patients treated with hypofractionated VMAT. The ART strategies included online and offline methods. The comprehensive analysis showed that daily on-line adaptation approaches were the most impactful. The findings of this study provided applicable insights into the selection of the optimal ART strategy, improving the quality of the decision-making process based on the quantitatively evaluated dosimetric benefits. The third study aimed to utilize a deep learning network to automatically contour critical organs on the computed tomography (CT) scans of head and neck cancer patients. Proposed model achieved expert level accuracy and was able to segment 25 critical organs on unseen CT images in approximately 7 seconds per patient. High accuracy and short contouring time allow for the implementation of the model within a clinical ART workflow, which would lead to a significant decrease in the time required to create a new adapted treatment plan. The objective of the fourth study was to use artificial intelligence methods to build a decision making support system that would classify previously delivered plans of brain tumor patients into those that met treatment planning objectives and those for which objectives were not met due to the priority given to one or more organs-at-risk. Among evaluated machine learning algorithms, the Logistic Regression model achieved the highest accuracy and can be used by radiation oncologists to support their decision-making process in terms of treatment plan adaptations and plan approvals in a data-driven quality assurance program.



Adaptive Radiation Therapy


Adaptive Radiation Therapy
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Author : X. Allen Li
language : en
Publisher: CRC Press
Release Date : 2011-01-27

Adaptive Radiation Therapy written by X. Allen Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-27 with Medical categories.


Modern medical imaging and radiation therapy technologies are so complex and computer driven that it is difficult for physicians and technologists to know exactly what is happening at the point-of-care. Medical physicists responsible for filling this gap in knowledge must stay abreast of the latest advances at the intersection of medical imaging an



Machine Learning In Magnetic Resonance Guided Adaptive Radiotherapy


Machine Learning In Magnetic Resonance Guided Adaptive Radiotherapy
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Author : Samuel Fransson
language : en
Publisher:
Release Date : 2024

Machine Learning In Magnetic Resonance Guided Adaptive Radiotherapy written by Samuel Fransson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.




Machine And Deep Learning In Oncology Medical Physics And Radiology


Machine And Deep Learning In Oncology Medical Physics And Radiology
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Author : Issam El Naqa
language : en
Publisher: Springer Nature
Release Date : 2022-02-02

Machine And Deep Learning In Oncology Medical Physics And Radiology written by Issam El Naqa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-02 with Science categories.


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 of applied machine learning communities.



Improving Cone Beam Computed Tomography Based Adaptive Radiation Therapy With Deep Learning


Improving Cone Beam Computed Tomography Based Adaptive Radiation Therapy With Deep Learning
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Author : Xiao Liang
language : en
Publisher:
Release Date : 2023

Improving Cone Beam Computed Tomography Based Adaptive Radiation Therapy With Deep Learning written by Xiao Liang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.




Machine Learning In Radiation Oncology


Machine Learning In Radiation Oncology
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Author : Issam El Naqa
language : en
Publisher: Springer
Release Date : 2015-06-19

Machine Learning In Radiation Oncology written by Issam El Naqa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-19 with Medical categories.


​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.



Machine Learning With Radiation Oncology Big Data


Machine Learning With Radiation Oncology Big Data
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Author : Jun Deng
language : en
Publisher: Frontiers Media SA
Release Date : 2019-01-21

Machine Learning With Radiation Oncology Big Data written by Jun Deng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-21 with categories.




Online Adaptive Mr Guided Radiotherapy


Online Adaptive Mr Guided Radiotherapy
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Author : Linda G. W. Kerkmeijer
language : en
Publisher: Frontiers Media SA
Release Date : 2021-10-18

Online Adaptive Mr Guided Radiotherapy written by Linda G. W. Kerkmeijer and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-18 with Medical categories.