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

Author(s)

Romano, Renan A. ; Pratavieira, Sebastiao ; da Silva, Ana P. ; Kurachi, Cristina ; Guimaraes, Francisco E. G. ; Beaurepaire, E ; Pavone, FS ; So, PTC

• Document type: Journal article
• Source: ADVANCES IN MICROSCOPIC IMAGING; v. 10414, p. 4-pg., 2017-01-01.

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. (AU)

• FAPESP's process: 09/54035-4 - Facility for advanced studies of biosystems and nanostructured materials
• Grantee: Igor Polikarpov
• Support Opportunities: Multi-user Equipment Program
• FAPESP's process: 13/07276-1 - CEPOF - Optics and Photonic Research Center
• Grantee: Vanderlei Salvador Bagnato
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 17/05722-5 - European Conferences on Biomedical Optics
• Grantee: Sebastião Pratavieira
• Support Opportunities: Research Grants - Meeting - Abroad