Artificial Intelligence and Deep Learning for Brachytherapy

IF 2.6 3区 医学 Q3 ONCOLOGY Seminars in Radiation Oncology Pub Date : 2022-10-01 DOI:10.1016/j.semradonc.2022.06.008
Xun Jia , Kevin Albuquerque
{"title":"Artificial Intelligence and Deep Learning for Brachytherapy","authors":"Xun Jia ,&nbsp;Kevin Albuquerque","doi":"10.1016/j.semradonc.2022.06.008","DOIUrl":null,"url":null,"abstract":"<div><p><span>In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems in brachytherapy<span>. 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, </span></span>outcome prediction<span>, 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.</span></p></div>","PeriodicalId":49542,"journal":{"name":"Seminars in Radiation Oncology","volume":"32 4","pages":"Pages 389-399"},"PeriodicalIF":2.6000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seminars in Radiation Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1053429622000376","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
近距离放射治疗的人工智能和深度学习
近年来,人工智能(AI),特别是基于深度学习(DL)的方法,已被广泛应用于解决近距离治疗中的各种问题。本文对人工智能/深度学习技术在近距离治疗中不同领域的最新发展和应用进行了全面的文献综述,包括图像增强、配准、分割、治疗计划、质量保证、结果预测等。这篇综述将强调与外部放射治疗相比,解决近距离治疗独特挑战的研究。与此同时,尽管取得了令人兴奋的成就,但我们也注意到,我们仍处于使用AI/ dl技术来增强近距离治疗临床实践的早期阶段。因此,本文也将提出挑战和未来的方向。我们希望这篇综述能激发对这一主题的讨论,并引发未来有影响力的研究,将技术进步转化为医疗保健效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
5.80
自引率
0.00%
发文量
48
审稿时长
>12 weeks
期刊介绍: Each issue of Seminars in Radiation Oncology is compiled by a guest editor to address a specific topic in the specialty, presenting definitive information on areas of rapid change and development. A significant number of articles report new scientific information. Topics covered include tumor biology, diagnosis, medical and surgical management of the patient, and new technologies.
期刊最新文献
Radiation as an Immune Modulator: Where We Are With Modern Total Body Irradiation. Radiation for Multiple Myeloma in the Era of Novel Agents: Indications, Safety, and Dose Selection. Rising to the Top: How Immune-Checkpoint Inhibitors are Changing the Landscape of Treatment for Classic Hodgkin Lymphoma. Translating Between Radiation Dose and Late Toxicity for Lymphoma Survivors: Implications on Toxicity Counseling and Survivorship. Advanced Stage Hodgkin and Diffuse Large B-Cell Lymphomas: Is There Still a Role for Consolidation Radiotherapy in the PET Era?
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1