Thesis title: Image processing on reconfigurable hardware for continuous monitoring of fluorescent biomarkers in cell cultures
Signal processing methods and tools for live cell imaging in fluorescence microscopy
Julien Ghaye, PhD student, EPFL-IC-LSI
Sandro Carrara, Lecturer and Senior Scientist, EPFL-IC-LSI
Keywords: fluorescence microscopy, image processing, biomarkers, lab-on-chip.
Monitoring live cells and studying their reactions to stimulus require us to use non invasive and non destructive instrumentations. Nowadays, one of the most used tool for this purpose is fluorescent microscopy, in which some fluorescent stains are used to label biological molecules and proteins. However the use of an optical system implies that the optical resolution is limited by the diffraction of light to approximately 200nm, which becomes challenging when the stained targets have to be detected on a nanometer scale. Some techniques such as confocal microscopy or photo activated localization microscopy increase the spatial resolution of the images but require either expensive/specialized equipments and/or special fluorescent stains.
The Nano-Tera project Nutrichip aims at developing an integrated lab-on-chip platform to investigate the effect of food ingestion by humans. The core of the system is an integrated chip, the NutriChip, which will be able to probe the health potential of dairy food samples, using a minimal biomarker set identified through in vivo and in vitro studies. The Nutrichip will feature an artificial microfluidic-based gastro intestinal tract, CMOS circuitry for optical detection and signal processing methods for real-time data analysis. Immunofluorescence will be used to stain proteins such as the Toll-Like receptors 2 and 4 to monitor the response of the immune system.
The goals of this work are first to develop and implement tools and image processing algorithms to quantify the immune response of the cells in the system, using a classical epi-fluorescence optical microscope. Second will be to embedded the developed signal processing methods into the Nutrichip Lab-on-Chip platform. The development technique within this project have to cope will limited space resolution of images and limited processing power to provide real-time feedback on the immune response of the cells.