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Conference Paper: Deep learning based fully automated pathology classification of lumbar spine

TitleDeep learning based fully automated pathology classification of lumbar spine
Authors
Kuang, XCheung, JPYZhang, T
Issue Date2021
PublisherInternational Society for the Study of the Lumbar Spine.
Citation
The International Society for the Study of the Lumbar Spine (ISSLS) Virtual Annual Meeting 2021: Reflecting the Past and Embracing the Future, 2-4 June 2021 How to Cite?
DescriptionGeneral Posters - Imaging, biomechanics, Artificial intelligence (AI) - no. GP149
Persistent Identifierhttp://hdl.handle.net/10722/300737

 

DC FieldValueLanguage
dc.contributor.authorKuang, X-
dc.contributor.authorCheung, JPY-
dc.contributor.authorZhang, T-
dc.date.accessioned2021-06-18T14:56:20Z-
dc.date.available2021-06-18T14:56:20Z-
dc.date.issued2021-
dc.identifier.citationThe International Society for the Study of the Lumbar Spine (ISSLS) Virtual Annual Meeting 2021: Reflecting the Past and Embracing the Future, 2-4 June 2021-
dc.identifier.urihttp://hdl.handle.net/10722/300737-
dc.descriptionGeneral Posters - Imaging, biomechanics, Artificial intelligence (AI) - no. GP149 -
dc.languageeng-
dc.publisherInternational Society for the Study of the Lumbar Spine. -
dc.relation.ispartofISSLS (International Society for the Study of the Lumbar Spine) Virtual Annual Meeting 2021-
dc.titleDeep learning based fully automated pathology classification of lumbar spine-
dc.typeConference_Paper-
dc.identifier.emailCheung, JPY: cheungjp@hku.hk-
dc.identifier.emailZhang, T: tgzhang@hku.hk-
dc.identifier.authorityCheung, JPY=rp01685-
dc.identifier.authorityZhang, T=rp02821-
dc.identifier.hkuros322956-

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