Artificial Intelligence in Radiation Oncology and Biomedical Physics
Series: Imaging in Medical Diagnosis and Therapy;
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29 348 Ft
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 13 April 2025
- ISBN 9780367556198
- Binding Paperback
- No. of pages184 pages
- Size 234x156 mm
- Weight 340 g
- Language English
- Illustrations 16 Illustrations, black & white; 30 Illustrations, color; 3 Halftones, black & white; 15 Halftones, color; 13 Line drawings, black & white; 15 Line drawings, color; 2 Tables, black & white 695
Categories
Short description:
This pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics.
MoreLong description:
This pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics.
AI and machine learning have attracted much recent attention and are being increasingly adopted in medicine, with many clinical components and commercial software including aspects of machine learning integration. General principles and important techniques in machine learning are introduced, followed by discussion of clinical applications, particularly in radiomics, outcome prediction, registration and segmentation, treatment planning, quality assurance, image processing, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is provided.
This book brings medical physicists and radiation oncologists up to date with the most novel applications of machine learning to medical physics. Practitioners will appreciate the insightful discussions and detailed descriptions in each chapter. Its emphasis on clinical applications reaches a wide audience within the medical physics profession.
MoreTable of Contents:
1. AI Applications in Radiation Therapy and Medical Physics 2. Machine Learning for Image-Based Radiotherapy Outcome Prediction 3. Metric Predictions for Machine and Patient-Specific Quality Assurance 4. Data-Driven Treatment Planning, Plan QA and Fast Dose Calculation 5. Reinforcement Learning for Radiation Therapy Planning and Image Processing 6. Image Registration and Segmentation 7. Motion Management and Image-Guided Radiation Therapy 8. Outlook of AI in Medical Physics and Radiation Oncology
More
Artificial Intelligence in Radiation Oncology and Biomedical Physics
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