An algorithm of blood typing using serological plate images

S. A. Korchagin, E. E. Zaychenkova, D. A. Sharapov,E. I. Ershov, Y. V. Butorin, Y. Y. Vengerov

COMPUTER OPTICS(2023)

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摘要
This paper describes an in vitro medical express diagnostic system designed to determine the blood group by analyzing the agglutination reaction (gluing of erythrocytes). The medical staff only needs to take a blood sample, put it on a serological plate, placing it in a special scanner for the blood group to be automatically determined. Data digitizing and machine-assisted plate identification allows two critical tasks to be addressed at once: storing the analysis results and controlling the human factor. The pro-posed recognition algorithm allows the alveolus boundaries to be accurately determined and the agglu-tination degree to be evaluated using a lightweight convolutional neural network. A unique dataset was collected with the independent assessment of agglutination degree conducted by medical experts. The agglutination estimation accuracy on the collected dataset of 3231 alveole was comparable to the accu-racy of an average medical expert and equal to 0.98.
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关键词
agglutination,blood typing,classification,Hough transform,deep learning
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