Deep learning for segmentation in radiation therapy planning: a review.
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| Title: | Deep learning for segmentation in radiation therapy planning: a review. |
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| Authors: | Samarasinghe G; School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia.; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia., Jameson M; Genesiscare, Sydney, New South Wales, Australia.; St Vincent's Clinical School, University of New South Wales, Sydney, New South Wales, Australia., Vinod S; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia., Field M; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia., Dowling J; Commonwealth Scientific and Industrial Research Organisation, Australian E-Health Research Centre, Herston, Queensland, Australia., Sowmya A; School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia., Holloway L; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia. |
| Source: | Journal of medical imaging and radiation oncology [J Med Imaging Radiat Oncol] 2021 Aug; Vol. 65 (5), pp. 578-595. Date of Electronic Publication: 2021 Jul 26. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Wiley-Blackwell Pub. Asia Country of Publication: Australia NLM ID: 101469340 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1754-9485 (Electronic) Linking ISSN: 17549477 NLM ISO Abbreviation: J Med Imaging Radiat Oncol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 34313006 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Deep learning for segmentation in radiation therapy planning: a review. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Samarasinghe+G%22">Samarasinghe G</searchLink>; School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia.; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.<br /><searchLink fieldCode="AU" term="%22Jameson+M%22">Jameson M</searchLink>; Genesiscare, Sydney, New South Wales, Australia.; St Vincent's Clinical School, University of New South Wales, Sydney, New South Wales, Australia.<br /><searchLink fieldCode="AU" term="%22Vinod+S%22">Vinod S</searchLink>; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia.<br /><searchLink fieldCode="AU" term="%22Field+M%22">Field M</searchLink>; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia.<br /><searchLink fieldCode="AU" term="%22Dowling+J%22">Dowling J</searchLink>; Commonwealth Scientific and Industrial Research Organisation, Australian E-Health Research Centre, Herston, Queensland, Australia.<br /><searchLink fieldCode="AU" term="%22Sowmya+A%22">Sowmya A</searchLink>; School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia.<br /><searchLink fieldCode="AU" term="%22Holloway+L%22">Holloway L</searchLink>; Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101469340%22">Journal of medical imaging and radiation oncology</searchLink> [J Med Imaging Radiat Oncol] 2021 Aug; Vol. 65 (5), pp. 578-595. <i>Date of Electronic Publication: </i>2021 Jul 26. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Review – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-Blackwell+Pub%2E+Asia%22">Wiley-Blackwell Pub. Asia </searchLink><i>Country of Publication: </i>Australia <i>NLM ID: </i>101469340 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1754-9485 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217549477%22">17549477 </searchLink><i>NLM ISO Abbreviation: </i>J Med Imaging Radiat Oncol <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=34313006 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/1754-9485.13286 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 578 Titles: – TitleFull: Deep learning for segmentation in radiation therapy planning: a review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Samarasinghe G – PersonEntity: Name: NameFull: Jameson M – PersonEntity: Name: NameFull: Vinod S – PersonEntity: Name: NameFull: Field M – PersonEntity: Name: NameFull: Dowling J – PersonEntity: Name: NameFull: Sowmya A – PersonEntity: Name: NameFull: Holloway L IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: 2021 Aug Type: published Y: 2021 Identifiers: – Type: issn-electronic Value: 1754-9485 Numbering: – Type: volume Value: 65 – Type: issue Value: 5 Titles: – TitleFull: Journal of medical imaging and radiation oncology Type: main |
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