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Pelvic Tumor Segmentation in MRI Images Using Deep Learning with DeepLabV3+ and U-Net: A Performance Comparison

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dc.contributor.correspondenceNobnop N.
dc.contributor.otherSrinakharinwirot University
dc.date.accessioned2025-05-28T07:55:03Z
dc.date.issued2024-01-01
dc.date.issuedBE2567-01-01
dc.identifier.citation16th Biomedical Engineering International Conference, BMEiCON 2024 (2024)
dc.identifier.doi10.1109/BMEiCON64021.2024.10896343
dc.identifier.scopus2-s2.0-105000417050
dc.identifier.urihttps://hdl.handle.net/20.500.14740/20172
dc.rights.holderSCOPUS
dc.subjectPhysics and Astronomy
dc.subjectEngineering
dc.subjectComputer Science
dc.titlePelvic Tumor Segmentation in MRI Images Using Deep Learning with DeepLabV3+ and U-Net: A Performance Comparison
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.title16th Biomedical Engineering International Conference, BMEiCON 2024
oairecerif.author.affiliationSrinakharinwirot University
swu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105000417050&origin=inward

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