TY - JOUR
T1 - Artificial intelligence in radiation oncology treatment planning
T2 - A brief overview
AU - Kiser, Kendall J.
AU - Fuller, Clifton D.
AU - Reed, Valerie K.
N1 - Publisher Copyright:
© Journal of Medical Artificial Intelligence. All rights reserved.
PY - 2019/5
Y1 - 2019/5
N2 - Among medical specialties, radiation oncology has long been an innovator and early adopter of therapeutic technologies. This specialty is now situated in prime position to be revolutionized by advances in artificial intelligence (AI), especially machine and deep learning. AI has been investigated by radiation oncologists and physicists in both general and niche radiotherapy planning tasks and has often demonstrated performance that is indistinguishable from human experts, while substantially shortening the time required to complete these tasks. We sought to review applications of AI to domains germane to radiation oncology, namely: image segmentation, treatment plan generation and optimization, normal tissue complication probability modeling, quality assurance (QA), and adaptive re-planning. We sought likewise to consider obstacles to AI adoption in the radiotherapy clinic, now primarily political, legal, and ethical rather than technical in nature.
AB - Among medical specialties, radiation oncology has long been an innovator and early adopter of therapeutic technologies. This specialty is now situated in prime position to be revolutionized by advances in artificial intelligence (AI), especially machine and deep learning. AI has been investigated by radiation oncologists and physicists in both general and niche radiotherapy planning tasks and has often demonstrated performance that is indistinguishable from human experts, while substantially shortening the time required to complete these tasks. We sought to review applications of AI to domains germane to radiation oncology, namely: image segmentation, treatment plan generation and optimization, normal tissue complication probability modeling, quality assurance (QA), and adaptive re-planning. We sought likewise to consider obstacles to AI adoption in the radiotherapy clinic, now primarily political, legal, and ethical rather than technical in nature.
KW - Artificial intelligence (AI)
KW - Computer assisted radiotherapy
KW - Image guided radiotherapy
KW - Machine learning
KW - Radiation oncology
UR - http://www.scopus.com/inward/record.url?scp=85073169138&partnerID=8YFLogxK
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U2 - 10.21037/jmai.2019.04.02
DO - 10.21037/jmai.2019.04.02
M3 - Review article
AN - SCOPUS:85073169138
SN - 2617-2496
VL - 2
JO - Journal of Medical Artificial Intelligence
JF - Journal of Medical Artificial Intelligence
IS - May
M1 - 9
ER -