File Download

There are no files associated with this item.

Supplementary

Conference Paper: A fully automatic deep learning method for upper airway segmentation and minimum cross-sectional area measurement on CBCT images

TitleA fully automatic deep learning method for upper airway segmentation and minimum cross-sectional area measurement on CBCT images
Authors
Chu, GGu, MLeung, YYYang, Y
Issue Date13-Mar-2023
Persistent Identifierhttp://hdl.handle.net/10722/337134

 

DC FieldValueLanguage
dc.contributor.authorChu, G-
dc.contributor.authorGu, M-
dc.contributor.authorLeung, YY-
dc.contributor.authorYang, Y-
dc.date.accessioned2024-03-11T10:18:22Z-
dc.date.available2024-03-11T10:18:22Z-
dc.date.issued2023-03-13-
dc.identifier.urihttp://hdl.handle.net/10722/337134-
dc.languageeng-
dc.relation.ispartof2023 AADOCR/CADR Annual Meeting (15/05/2023-18/05/2023, Portland, Oregon)-
dc.titleA fully automatic deep learning method for upper airway segmentation and minimum cross-sectional area measurement on CBCT images-
dc.typeConference_Paper-

Export via OAI-PMH Interface in XML Formats

OR

Export to Other Non-XML Formats