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Article: Current landscape and potential future applications of artificial intelligence in medical physics and radiotherapy
Title | Current landscape and potential future applications of artificial intelligence in medical physics and radiotherapy |
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Authors | |
Keywords | Artificial intelligence Medical physics Radiotherapy Image acquisition Image segmentation |
Issue Date | 2021 |
Publisher | Baishideng Publishing Group Co., Limited. The Journal's web site is located at https://www.wjgnet.com/2644-3260/index.htm |
Citation | Artificial Intelligence in Medical Imaging, 2021, v. 2 n. 2, p. 37-55 How to Cite? |
Abstract | Artificial intelligence (AI) has seen tremendous growth over the past decade and stands to disrupts the medical industry. In medicine, this has been applied in medical imaging and other digitised medical disciplines, but in more traditional fields like medical physics, the adoption of AI is still at an early stage. Though AI is anticipated to be better than human in certain tasks, with the rapid growth of AI, there is increasing concerns for its usage. The focus of this paper is on the current landscape and potential future applications of artificial intelligence in medical physics and radiotherapy. Topics on AI for image acquisition, image segmentation, treatment delivery, quality assurance and outcome prediction will be explored as well as the interaction between human and AI. This will give insights into how we should approach and use the technology for enhancing the quality of clinical practice. |
Persistent Identifier | http://hdl.handle.net/10722/301228 |
ISSN |
DC Field | Value | Language |
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dc.contributor.author | Ip, WY | - |
dc.contributor.author | Yeung, FK | - |
dc.contributor.author | Yung, SPF | - |
dc.contributor.author | Yu, HCJ | - |
dc.contributor.author | So, TH | - |
dc.contributor.author | Vardhanabhuti, V | - |
dc.date.accessioned | 2021-07-27T08:08:01Z | - |
dc.date.available | 2021-07-27T08:08:01Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Artificial Intelligence in Medical Imaging, 2021, v. 2 n. 2, p. 37-55 | - |
dc.identifier.issn | 2644-3260 | - |
dc.identifier.uri | http://hdl.handle.net/10722/301228 | - |
dc.description.abstract | Artificial intelligence (AI) has seen tremendous growth over the past decade and stands to disrupts the medical industry. In medicine, this has been applied in medical imaging and other digitised medical disciplines, but in more traditional fields like medical physics, the adoption of AI is still at an early stage. Though AI is anticipated to be better than human in certain tasks, with the rapid growth of AI, there is increasing concerns for its usage. The focus of this paper is on the current landscape and potential future applications of artificial intelligence in medical physics and radiotherapy. Topics on AI for image acquisition, image segmentation, treatment delivery, quality assurance and outcome prediction will be explored as well as the interaction between human and AI. This will give insights into how we should approach and use the technology for enhancing the quality of clinical practice. | - |
dc.language | eng | - |
dc.publisher | Baishideng Publishing Group Co., Limited. The Journal's web site is located at https://www.wjgnet.com/2644-3260/index.htm | - |
dc.relation.ispartof | Artificial Intelligence in Medical Imaging | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Artificial intelligence | - |
dc.subject | Medical physics | - |
dc.subject | Radiotherapy | - |
dc.subject | Image acquisition | - |
dc.subject | Image segmentation | - |
dc.title | Current landscape and potential future applications of artificial intelligence in medical physics and radiotherapy | - |
dc.type | Article | - |
dc.identifier.email | Ip, WY: wiip0817@hku.hk | - |
dc.identifier.email | Yung, SPF: spfy@hku.hk | - |
dc.identifier.email | Vardhanabhuti, V: varv@hku.hk | - |
dc.identifier.authority | So, TH=rp01981 | - |
dc.identifier.authority | Vardhanabhuti, V=rp01900 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.35711/aimi.v2.i2.37 | - |
dc.identifier.hkuros | 323407 | - |
dc.identifier.volume | 2 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 37 | - |
dc.identifier.epage | 55 | - |
dc.publisher.place | United States | - |