Deep learning-enabled fluorescence imaging for oral cancer margin classification in preclinical models.

Saved in:

Bibliographic Details
Title:	Deep learning-enabled fluorescence imaging for oral cancer margin classification in preclinical models.
Authors:	Kurosawa H; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada., Won NJ; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada., Wunder JB; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada., Patil S; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada., Bartling M; University of Toronto, Department of Otolaryngology-Head and Neck Surgery, Toronto, Ontario, Canada., Najjar E; University of Toronto, Department of Otolaryngology-Head and Neck Surgery, Toronto, Ontario, Canada., Tzelnick S; University of Toronto, Department of Otolaryngology-Head and Neck Surgery, Toronto, Ontario, Canada., Wilson BC; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.; University of Toronto, Department of Medical Biophysics, Toronto, Ontario, Canada., Irish JC; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.; University of Toronto, Department of Otolaryngology-Head and Neck Surgery, Toronto, Ontario, Canada., Daly MJ; University Health Network, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
Source:	Journal of biomedical optics [J Biomed Opt] 2025 Dec; Vol. 30 (Suppl 3), pp. S34109. Date of Electronic Publication: 2025 Sep 12.
Publication Type:	Journal Article
Journal Info:	Publisher: Published by SPIE--the International Society for Optical Engineering in cooperation with International Biomedical Optics Society Country of Publication: United States NLM ID: 9605853 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1560-2281 (Electronic) Linking ISSN: 10833668 NLM ISO Abbreviation: J Biomed Opt Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1560-2281
DOI:	10.1117/1.JBO.30.S3.S34109