Brain Hemorrhage Segmentation in CT Scan Images using Deep Learning based Approach

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dc.contributor.authorZhang H.
dc.contributor.authorKusakunniran W.
dc.contributor.authorSiriapisith T.
dc.contributor.authorSaiviroonporn P.
dc.contributor.otherMahidol University
dc.date.accessioned2023-06-18T17:02:43Z
dc.date.available2023-06-18T17:02:43Z
dc.date.issued2022-01-01
dc.description.abstractIn this paper, a variety of neural networks are compared, and the optimal CE-Net model is found and improved. It can segment CT images of cerebral hemorrhage, especially for the small and irregular images.
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON Vol.2022-November (2022)
dc.identifier.doi10.1109/TENCON55691.2022.9977491
dc.identifier.eissn21593450
dc.identifier.issn21593442
dc.identifier.scopus2-s2.0-85145657571
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/84322
dc.rights.holderSCOPUS
dc.subjectComputer Science
dc.titleBrain Hemorrhage Segmentation in CT Scan Images using Deep Learning based Approach
dc.typeConference Paper
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85145657571&origin=inward
oaire.citation.titleIEEE Region 10 Annual International Conference, Proceedings/TENCON
oaire.citation.volume2022-November
oairecerif.author.affiliationSiriraj Hospital
oairecerif.author.affiliationMahidol University

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