6533b82cfe1ef96bd128fbe9

RESEARCH PRODUCT

Robust image analysis methods for the detection and the characterization of compact objects : application to biology

Ambroise Marin

subject

Detection[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyCaracterisation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingCharacterizationImage[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingBiologyBiologie[SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing

description

In the field of microbiology, many experiments are based on a fine observation of microorganisms. Because of their interest in the development of modern agri-food processes, it is important to study their development and survival rate under specific environmental conditions such as osmotic or thermal stress. Microscopic imaging is one of the most used tools for observing microorganisms. The manual interpretation of acquired images raises problems of subjectivity, cost and reproducibility. This thesis proposes the development of standardized image analysis tools allowing the interpretation of images at two scales:- At the scale of the observation slide: the use of specific counting slides (Malassez) allows, from the counting of the cells present in the zone of interest of the slide, to deduce the cell concentration of a solution of Saccharomyces cerevisiae subjected to osmotic stress. The tools developed allow for the identification and characterization of this area of interest (grid) and precise counting of the cells.- At the cell scale: a mutant strain of Saccharomyces cerevisiae allows for the observation in fluorescence the Pab1p-GFP protein involved in the formation of intracellular ribo-nucleoprotein aggregates consecutive to thermal stress. The tools developed allows for obtaining a statistical view of the development of these aggregates by automating the estimation of their number for a very large number of cells.

https://theses.hal.science/tel-02191661