Texture analysis of deep ultraviolet fluorescence images for intraoperative assessment of breast tumor margins

Tongtong Lu; Julie Jorns; Mollie Patton; Renee Fisher; Amanda Emmrich; Taly Gilat-Schmidt; Dong Hye Ye; Tina Yen; Bing Yu

doi:10.1364/NTM.2021.NM2C.3

Biophotonics Congress 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper NM2C.3
•https://doi.org/10.1364/NTM.2021.NM2C.3

Texture analysis of deep ultraviolet fluorescence images for intraoperative assessment of breast tumor margins

Tongtong Lu, Julie Jorns, Mollie Patton, Renee Fisher, Amanda Emmrich, Taly Gilat-Schmidt, Dong Hye Ye, Tina Yen, and Bing Yu

Novel Techniques in Microscopy 2021

Washington, DC United States
12–16 April 2021
ISBN: 978-1-943580-85-9

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Light Sheet and Ultra-violet Microscopies (NM2C)

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T. Lu, J. Jorns, M. Patton, R. Fisher, A. Emmrich, T. Gilat-Schmidt, D. H. Ye, T. Yen, and B. Yu, "Texture analysis of deep ultraviolet fluorescence images for intraoperative assessment of breast tumor margins," in Biophotonics Congress 2021, C. Boudoux, K. Maitland, C. Hendon, M. Wojtkowski, K. Quinn, M. Schanne-Klein, N. Durr, D. Elson, F. Cichos, L. Oddershede, V. Emiliani, O. Maragò, S. Nic Chormaic, N. Pégard, S. Gibbs, S. Vinogradov, M. Niedre, K. Samkoe, A. Devor, D. Peterka, P. Blinder, and E. Buckley, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper NM2C.3.

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Abstract

Deep ultraviolet (DUV) excitation has generated high-resolution fluorescence images of fresh and unfixed breast tissues. We report that texture analysis of DUV images can potentially differentiate malignant samples from normal breast tissues.

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