PYTHON INTERFACE DESIGN FOR MICROPHOTOGRAPHY ANALYSIS:APPLICATION TO EVALUATE THE HEMORHEOLOGICAL ACTIVITY OF QUERCETIN

This work describes the development of a GUI (Graphic User Interface) in Python to systematize the image analysis within the framework of the in vitro hemorheological study of phytochemicals that could be used for diabetes treatment. The usability criteria of the GUI based on the TkInter library are aimed at non-expert users. The image processing algorithms are contained in the OpenCV2 library, which uses pre-trained neural networks. Images were obtained using a digital camera coupled to an inverted microscope (40x objective). In this work, the parameter search process was optimized (percentages of isolated cells and the coefficient of isolated cells) for red blood cells incubated with quercetin solutions at different concentrations.