TY - JOUR
T1 - Artificial Intelligence and Deep Learning for Brachytherapy
AU - Jia, Xun
AU - Albuquerque, Kevin
N1 - Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022
Y1 - 2022
N2 - In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems in brachytherapy. This paper presents a comprehensive literature review on recent developments and applications of AI/DL technologies for different areas in brachytherapy, including image enhancement, registration, segmentation, treatment planning, quality assurance, outcome prediction, etc. The review will emphasize studies addressing unique challenges in brachytherapy, as compared to external beam radiotherapy. Meanwhile, despite exciting achievements, it is also noted that we are still at the early stage of employing AI/DL-technologies to enhance brachytherapy clinical practice. Hence, this paper will also present challenges and future directions. We hope this review will inspire discussions on this topic and trigger future impactful studies to transform technology advancements into healthcare benefits.
AB - In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems in brachytherapy. This paper presents a comprehensive literature review on recent developments and applications of AI/DL technologies for different areas in brachytherapy, including image enhancement, registration, segmentation, treatment planning, quality assurance, outcome prediction, etc. The review will emphasize studies addressing unique challenges in brachytherapy, as compared to external beam radiotherapy. Meanwhile, despite exciting achievements, it is also noted that we are still at the early stage of employing AI/DL-technologies to enhance brachytherapy clinical practice. Hence, this paper will also present challenges and future directions. We hope this review will inspire discussions on this topic and trigger future impactful studies to transform technology advancements into healthcare benefits.
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U2 - 10.1016/j.semradonc.2022.06.008
DO - 10.1016/j.semradonc.2022.06.008
M3 - Review article
C2 - 36202441
AN - SCOPUS:85134836731
SN - 1053-4296
JO - Seminars in Radiation Oncology
JF - Seminars in Radiation Oncology
ER -