Artificial Intelligence in Radiation Oncology and Biomedical Physics
暫譯: 放射腫瘤學與生物醫學物理中的人工智慧
Valdes, Gilmer, Xing, Lei
- 出版商: CRC
- 出版日期: 2023-08-14
- 售價: $6,680
- 貴賓價: 9.5 折 $6,346
- 語言: 英文
- 頁數: 172
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367538105
- ISBN-13: 9780367538101
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相關分類:
人工智慧、物理學 Physics
海外代購書籍(需單獨結帳)
商品描述
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.
商品描述(中文翻譯)
這本開創性的書籍探討了機器學習及其他人工智慧技術如何影響數百萬名受益於電離輻射的癌症患者。書中匯集了來自全球的研究者和臨床醫生的貢獻，重點關注機器學習在醫學物理中的臨床應用。
人工智慧和機器學習最近受到廣泛關注，並在醫學中越來越多地被採用，許多臨床組件和商業軟體都包含機器學習整合的元素。書中介紹了機器學習的一般原則和重要技術，隨後討論了臨床應用，特別是在放射組學、結果預測、配準與分割、治療計劃、質量保證、影像處理和臨床決策等方面。最後，書中提供了對人工智慧在放射腫瘤學中角色的未來展望。
這本書使醫學物理學家和放射腫瘤科醫生了解機器學習在醫學物理中最前沿的應用。從業者將會欣賞每一章中的深刻討論和詳細描述。其對臨床應用的強調使其在醫學物理專業中吸引了廣泛的讀者群。
作者簡介
Dr. Gilmer Valdes received his PhD in medical physics from the University of California, Los Angeles, in 2013. He was a postdoctoral fellow with the University of California, San Francisco between 2013-2014 and a medical physics resident from 2014 to 2016 with the University of Pennsylvania. He is currently an associate professor with dual appointments in the Department of Radiation Oncology and the Department of Epidemiology and Biostatistics at the University of California, San Francisco. His main research focus is in the development of algorithms to satisfy special needs that machine learning applications have in medicine.
Dr. Lei Xing is the Jacob Haimson & Sarah S. Donaldson Professor and Director of Medical Physics Division of Radiation Oncology Department at Stanford University School of Medicine. He also holds affiliate faculty positions in the Department of Electrical Engineering, Biomedical Informatics, Bio-X and Molecular Imaging Program at Stanford (MIPS). Dr. Xing obtained his PhD in Physics from the Johns Hopkins University and received his medical physics training at the University of Chicago. His research has been focused on artificial intelligence in medicine, medical imaging, treatment planning and dose optimization, medical imaging, imaging instrumentations, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. He has made unique and significant contributions to each of the above areas. Dr. Xing is an author on more than 400 peer reviewed publications, an inventor/co-inventor on many issued and pending patents, and a co- investigator or principal investigator on numerous NIH, DOD, NSF, RSNA, AAPM, Komen, ACS and corporate grants. He is a fellow of AAPM (American Association of Physicists in Medicine) and AIMBE (American Institute for Medical and Biological Engineering).
作者簡介(中文翻譯)
吉爾默·瓦爾德斯博士於2013年在加州大學洛杉磯分校獲得醫學物理學博士學位。他在2013至2014年間擔任加州大學舊金山分校的博士後研究員，並於2014至2016年間在賓夕法尼亞大學擔任醫學物理住院醫師。目前，他是加州大學舊金山分校放射腫瘤學系及流行病學與生物統計學系的副教授。他的主要研究重點是開發算法，以滿足機器學習在醫學應用中的特殊需求。
雷·辛博士是史丹佛大學醫學院放射腫瘤學系醫學物理學部的雅各布·海姆森與莎拉·S·唐納森教授及主任。他同時在史丹佛大學的電機工程系、生物醫學資訊學系、生物科學計畫及分子影像計畫擔任附屬教職。辛博士在約翰霍普金斯大學獲得物理學博士學位，並在芝加哥大學接受醫學物理訓練。他的研究專注於醫學中的人工智慧、醫學影像、治療計畫與劑量優化、醫學影像、影像儀器、影像引導介入、奈米醫學以及分子影像在放射腫瘤學中的應用。他在上述每個領域均有獨特且重要的貢獻。辛博士是400多篇經過同行評審的出版物的作者，許多已發及待發專利的發明人/共同發明人，並在多項NIH、DOD、NSF、RSNA、AAPM、科門、ACS及企業贊助的研究計畫中擔任共同研究者或主要研究者。他是AAPM（美國醫學物理學會）及AIMBE（美國醫學與生物工程學會）的會士。
