An algorithm of blood typing using serological plate images
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...
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| Format: | Article |
| Language: | English |
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Samara National Research University
2023-12-01
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| Series: | Компьютерная оптика |
| Subjects: | |
| Online Access: | https://www.computeroptics.ru/eng/KO/Annot/KO47-6/470613e.html |
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| author | S.A. Korchagin E.E. Zaychenkova D.A. Sharapov E.I. Ershov Y.V. Butorin Y.Y. Vengerov |
| author_facet | S.A. Korchagin E.E. Zaychenkova D.A. Sharapov E.I. Ershov Y.V. Butorin Y.Y. Vengerov |
| author_sort | S.A. Korchagin |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ec2a08e67191484185f0f06b7267ff9a |
| institution | Kabale University |
| issn | 0134-2452 2412-6179 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Samara National Research University |
| record_format | Article |
| series | Компьютерная оптика |
| spelling | doaj-art-ec2a08e67191484185f0f06b7267ff9a2025-01-30T10:55:17ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792023-12-0147695896710.18287/2412-6179-CO-1339An algorithm of blood typing using serological plate imagesS.A. Korchagin0E.E. Zaychenkova1D.A. Sharapov2E.I. Ershov3Y.V. Butorin4Y.Y. Vengerov5The Institute for Information Transmission Problems; Lomonosov Moscow State UniversityThe Institute for Information Transmission Problems; The Moscow Institute of Physics and TechnologyThe Institute for Information Transmission Problems; The Moscow Institute of Physics and TechnologyThe Institute for Information Transmission Problems; The Moscow Institute of Physics and TechnologyThe Institute for Information Transmission Problems; Lomonosov Moscow State University; LLC «SYNTECO»The Institute for Information Transmission Problems; Lomonosov Moscow State University; LLC «SYNTECO»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.https://www.computeroptics.ru/eng/KO/Annot/KO47-6/470613e.htmlagglutinationblood typingclassificationhough transformdeep learning |
| spellingShingle | S.A. Korchagin E.E. Zaychenkova D.A. Sharapov E.I. Ershov Y.V. Butorin Y.Y. Vengerov An algorithm of blood typing using serological plate images Компьютерная оптика agglutination blood typing classification hough transform deep learning |
| title | An algorithm of blood typing using serological plate images |
| title_full | An algorithm of blood typing using serological plate images |
| title_fullStr | An algorithm of blood typing using serological plate images |
| title_full_unstemmed | An algorithm of blood typing using serological plate images |
| title_short | An algorithm of blood typing using serological plate images |
| title_sort | algorithm of blood typing using serological plate images |
| topic | agglutination blood typing classification hough transform deep learning |
| url | https://www.computeroptics.ru/eng/KO/Annot/KO47-6/470613e.html |
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