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

Authors

  • Patricia Buszniez Facultad de Ciencias Bioquímicas y Farmacéuticas (UNR) - Suipacha 531, Rosario – Argentina
  • Manuela Gomez Facultad de Ciencias Bioquímicas y Farmacéuticas (UNR) - Suipacha 531, Rosario – Argentina
  • Horacio Castellini Facultad de Cs. Exactas, Ingeniería y Agrimensura (UNR) – Rosario – Argentina
  • Bibiana D Riquelme Facultad de Ciencias Bioquímicas y Farmacéuticas (UNR) - Suipacha 531, Rosario – Argentina Grupo de Física Biomédica, Instituto de Física Rosario (CONICET-UNR) – Rosario – Argentina Consejo de Investigaciones de la UNR – Argentina

Abstract

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.

Keywords: graphic user interface, python, quercetin, diabetes.

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Published

2024-12-30

Issue

Vol. 35 No. 4 (2024): Anales AFA

Section

Física Aplicada