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  4. Publikationen School of Engineering
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-29674
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dc.contributor.authorJermain, Peter R.-
dc.contributor.authorOswald, Martin-
dc.contributor.authorLangdun, Tenzin-
dc.contributor.authorWright, Santana-
dc.contributor.authorKhan, Ashraf-
dc.contributor.authorStadelmann, Thilo-
dc.contributor.authorAbdulkadir, Ahmed-
dc.contributor.authorYaroslavsky, Ann N.-
dc.date.accessioned2024-01-27T13:50:02Z-
dc.date.available2024-01-27T13:50:02Z-
dc.date.issued2024-04-07-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/29674-
dc.description.abstractWe 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.de_CH
dc.language.isoende_CH
dc.publisherOptica Publishing Groupde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectDeep learningde_CH
dc.subjectMedical imagingde_CH
dc.subjectCancer therapyde_CH
dc.subjectAIde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleRapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesionsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitCentre for Artificial Intelligence (CAI)de_CH
dc.identifier.doi10.21256/zhaw-29674-
zhaw.conference.detailsOptica Biophotonics Congress: Biomedical Optics, Fort Lauderdale, USA, 7-10 April 2024de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsProceedings of the 2024 Optica Biophotonics Congress: Biomedical Opticsde_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedDigital Health Labde_CH
zhaw.webfeedMachine Perception and Cognitionde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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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.


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