Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues

Hulya Torun; Numan Batur; Buse Bilgin; Omer Tarik Esengur; Kemal Baysal; Ibrahim Kulac; Ihsan Solaroglu; Mehmet Cengiz Onbasli

doi:10.1117/12.2608957

Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues

Hulya Torun
, Numan Batur
, Buse Bilgin
, Omer Tarik Esengur
, Kemal Baysal
, Ibrahim Kulac
, Ihsan Solaroglu
, Mehmet Cengiz Onbasli

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Multiscale Imaging and Spectroscopy III
Editors	Paul J. Campagnola, Kristen C. Maitland, Darren M. Roblyer
Publisher	SPIE
ISBN (Electronic)	9781510647596
DOIs	https://doi.org/10.1117/12.2608957
State	Published - Mar 4 2022
Externally published	Yes
Event	Multiscale Imaging and Spectroscopy III 2022 - Virtual, Online Duration: Feb 20 2022 → Feb 24 2022

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	11944
ISSN (Print)	1605-7422

Conference

Conference	Multiscale Imaging and Spectroscopy III 2022
City	Virtual, Online
Period	2/20/22 → 2/24/22

ASJC Scopus Subject Areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Biomaterials
Radiology Nuclear Medicine and imaging

Keywords

Glioblastoma
Raman spectra classification
Raman spectroscopy
brain cancer
brain tumor
machine learning
tissue identification
white matter

Access to Document

10.1117/12.2608957

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Torun, H., Batur, N., Bilgin, B., Esengur, O. T., Baysal, K., Kulac, I., Solaroglu, I., & Onbasli, M. C. (2022). Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues. In P. J. Campagnola, K. C. Maitland, & D. M. Roblyer (Eds.), Multiscale Imaging and Spectroscopy III Article 1194406 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11944). SPIE. https://doi.org/10.1117/12.2608957

Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues. / Torun, Hulya; Batur, Numan; Bilgin, Buse et al.
Multiscale Imaging and Spectroscopy III. ed. / Paul J. Campagnola; Kristen C. Maitland; Darren M. Roblyer. SPIE, 2022. 1194406 (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 11944).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Torun, H, Batur, N, Bilgin, B, Esengur, OT, Baysal, K, Kulac, I, Solaroglu, I & Onbasli, MC 2022, Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues. in PJ Campagnola, KC Maitland & DM Roblyer (eds), Multiscale Imaging and Spectroscopy III., 1194406, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 11944, SPIE, Multiscale Imaging and Spectroscopy III 2022, Virtual, Online, 2/20/22. https://doi.org/10.1117/12.2608957

Torun H, Batur N, Bilgin B, Esengur OT, Baysal K, Kulac I et al. Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues. In Campagnola PJ, Maitland KC, Roblyer DM, editors, Multiscale Imaging and Spectroscopy III. SPIE. 2022. 1194406. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE). doi: 10.1117/12.2608957

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Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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