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An algorithm of blood typing using serological plate images
S.A. Korchagin 1,2, E.E. Zaychenkova 1,3, D.A. Sharapov 1,3, E.I. Ershov 1,3, Y.V. Butorin 1,2,4, Y.Y. Vengerov 1,2,4

1 The Institute for Information Transmission Problems,
127051, Moscow, Russia, Bolshoy Karetny per. 19, build 1;
2 Lomonosov Moscow State University,
119991, Moscow, Russia, Leninskie Gory 1;
3 The Moscow Institute of Physics and Technology,
141701, Russia, Moscow region, Dolgoprudny, Institutskiy per. 9;
4 LLC «SYNTECO», 142530, Russia, Moscow region, Elektrogorsk, Budionova 1a

 PDF, 3851 kB

DOI: 10.18287/2412-6179-CO-1339

Pages: 958-967.

Full text of article: Russian language.

Abstract:
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 proposed recognition algorithm allows  the alveolus boundaries to be accurately determined and the agglutination 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 accuracy of an average medical expert and equal to 0.98.

Keywords:
agglutination, blood typing, classification, Hough transform, deep learning.

Citation:
Korchagin SA, Zaychenkova EE, Sharapov DA, Ershov EI, Butorin UV, Vengerov UU. An algorithm of blood typing using serological plate images. Computer Optics 2023; 47(6): 958-967. DOI: 10.18287/2412-6179-CO-1339.

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