Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions

Jermain, Peter R.; Oswald, Martin; Langdun, Tenzin; Wright, Santana; Khan, Ashraf; Stadelmann, Thilo; Abdulkadir, Ahmed; Yaroslavsky, Ann N.

doi:10.21256/zhaw-29674

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-29674

Publication type:	Conference paper
Type of review:	Peer review (publication)
Title:	Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions
Authors:	Jermain, Peter R. Oswald, Martin Langdun, Tenzin Wright, Santana Khan, Ashraf Stadelmann, Thilo Abdulkadir, Ahmed Yaroslavsky, Ann N.
et. al:	No
DOI:	10.21256/zhaw-29674
Proceedings:	Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics
Conference details:	Optica Biophotonics Congress: Biomedical Optics, Fort Lauderdale, USA, 7-10 April 2024
Issue Date:	7-Apr-2024
Publisher / Ed. Institution:	Optica Publishing Group
Language:	English
Subjects:	Deep learning; Medical imaging; Cancer therapy; AI
Subject (DDC):	006: Special computer methods
Abstract:	We have developed and implemented a rapid, robust, and clinically viable protocol for fluorescence polarization cytopathology of thyroid nodules. The proposed approach utilizes rapid sample preparation and automated image analysis to accurately diagnose thyroid cancer.
URI:	https://digitalcollection.zhaw.ch/handle/11475/29674
Fulltext version:	Accepted version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Centre for Artificial Intelligence (CAI)
Appears in collections:	Publikationen School of Engineering

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Jermain, P. R., Oswald, M., Langdun, T., Wright, S., Khan, A., Stadelmann, T., Abdulkadir, A., & Yaroslavsky, A. N. (2024, April 7). Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions. Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics. https://doi.org/10.21256/zhaw-29674

Jermain, P.R. et al. (2024) ‘Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions’, in Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics. Optica Publishing Group. Available at: https://doi.org/10.21256/zhaw-29674.

P. R. Jermain et al., “Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions,” in Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics, Apr. 2024. doi: 10.21256/zhaw-29674.

JERMAIN, Peter R., Martin OSWALD, Tenzin LANGDUN, Santana WRIGHT, Ashraf KHAN, Thilo STADELMANN, Ahmed ABDULKADIR und Ann N. YAROSLAVSKY, 2024. Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions. In: Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics. Conference paper. Optica Publishing Group. 7 April 2024

Jermain, Peter R., Martin Oswald, Tenzin Langdun, Santana Wright, Ashraf Khan, Thilo Stadelmann, Ahmed Abdulkadir, and Ann N. Yaroslavsky. 2024. “Rapid Optical Cytology with Deep Learning-Based Cell Segmentation for Diagnosis of Thyroid Lesions.” Conference paper. In Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics. Optica Publishing Group. https://doi.org/10.21256/zhaw-29674.

Jermain, Peter R., et al. “Rapid Optical Cytology with Deep Learning-Based Cell Segmentation for Diagnosis of Thyroid Lesions.” Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics, Optica Publishing Group, 2024, https://doi.org/10.21256/zhaw-29674.