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EN
Chromatoelectrophoresis is a laboratory technique which depicts changes in multiple protein fractions inclusively. The combined, simultaneous analysis based on two key protein features (charge and molecular weight) offers a unique opportunity for better understanding of serum protein composition as well as it indicates the fraction which needs more thorough investigation. Because of those promising features, the chromatoelectrophoresis with automated analysis is expected to be a valuable laboratory test, aiding the process of medical diagnosis. However, without information technology support, analyzing the results of chromatoelectrophoresis would be tedious and time-consuming. For better optimization, both an algorithm for output image analysis and application with user-friendly interface were developed. Planning, development and testing were conducted at AGH University of Science and Technology and Jagiellonian University, Medical College in Cracow, Poland. With this article, we present the results of the first year of cooperation, code-named ChromSee.org project. The algorithm for distinguishing, naming and analyzing the content of fractions, the application and their utility in real-life settings are described, as well as potential future developments.
PL
W artykule opisano proces elektroforezy białek osocza ludzkiej krwi oraz wykorzystanie badania w diagnostyce chorób. Przedstawiona została koncepcja rozwijanej w ostatnich latach innowacyjnej techniki rozszerzonej elektroforezy, która ma na celu poprawę wykrywalności schorzeń. Zaprezentowany został również prototyp algorytmu wyodrębniania poszczególnych frakcji na podstawie analizy obrazu. Algorytm sprawdza kolejne poziomy szarości pikseli obrazu oraz wykorzystuje informacje o poziomie szarości kontekstu danego piksela.
EN
The article explains the process of human serum protein electrophoresis and its usage in diseases diagnostics. A basic concept of the extended electrophoresis is presented - an innovative and intensively developed diagnostic technique, which purpose is to increase the effectiveness of illnesses detection. The paper presents the prototype of an algorithm to differentiate serum fractions, which bases on image analysis. The algorithm scans the image in accordance with pixels' grayscale levels and uses the contextual grayscale values of the processed pixel.
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