Multispectral confocal microscopy images and artificial neural nets to monitor the photosensitizer uptake and degradation in Candida albicans cells

Renan A. Romano; Sebastião Pratavieira; Ana P. da Silva; Cristina Kurachi; Francisco E. G. Guimarães

doi:10.1117/12.2282806

28 July 2017 Multispectral confocal microscopy images and artificial neural nets to monitor the photosensitizer uptake and degradation in Candida albicans cells

Renan A. Romano, Sebastião Pratavieira, Ana P. da Silva, Cristina Kurachi, Francisco E. G. Guimarães

Author Affiliations +

Proceedings Volume 10414, Advances in Microscopic Imaging; 104140D (2017) https://doi.org/10.1117/12.2282806
Event: European Conferences on Biomedical Optics, 2017, Munich, Germany

Abstract

This study clearly demonstrates that multispectral confocal microscopy images analyzed by artificial neural networks provides a powerful tool to real-time monitoring photosensitizer uptake, as well as photochemical transformations occurred.

Citation Download Citation

Renan A. Romano, Sebastião Pratavieira, Ana P. da Silva, Cristina Kurachi, and Francisco E. G. Guimarães "Multispectral confocal microscopy images and artificial neural nets to monitor the photosensitizer uptake and degradation in Candida albicans cells", Proc. SPIE 10414, Advances in Microscopic Imaging, 104140D (28 July 2017); https://doi.org/10.1117/12.2282806

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