Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images
The method of classification of erythrocytes (red blood cells) based on spectral features of the cell surface images (of physical-mechanical properties maps) obtained with an atomic-force microscope (AFM) is proposed. Each scan line of the original AFM image is considered as a random sequence realiz...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Russian |
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The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
2019-09-01
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| Series: | Informatika |
| Subjects: | |
| Online Access: | https://inf.grid.by/jour/article/view/871 |
| _version_ | 1797877254780354560 |
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| author | I. E. Starodubtsev Yu. S. Kharin M. S. Abramovich |
| author_facet | I. E. Starodubtsev Yu. S. Kharin M. S. Abramovich |
| author_sort | I. E. Starodubtsev |
| collection | DOAJ |
| description | The method of classification of erythrocytes (red blood cells) based on spectral features of the cell surface images (of physical-mechanical properties maps) obtained with an atomic-force microscope (AFM) is proposed. Each scan line of the original AFM image is considered as a random sequence realization and the discrete Fourier transform is applied to compute its spectral features. The spectral estimates are smoothed on the map and the informative characteristics are computed as the medians of the spectrogram values for each frequency. The classification or two classes of erythrocytes (spherocytes and discocytes) taken from patients with hereditary spherocytosis was carried out by the obtained informative characteristics using the decision trees and boosted decision trees methods. The frequency interval was found with the best classification accuracy – over 82 % for the boosted decision trees method. |
| first_indexed | 2024-04-10T02:14:05Z |
| format | Article |
| id | doaj.art-8a0d02af740a4e19bb46606ef395245b |
| institution | Directory Open Access Journal |
| issn | 1816-0301 |
| language | Russian |
| last_indexed | 2024-04-10T02:14:05Z |
| publishDate | 2019-09-01 |
| publisher | The United Institute of Informatics Problems of the National Academy of Sciences of Belarus |
| record_format | Article |
| series | Informatika |
| spelling | doaj.art-8a0d02af740a4e19bb46606ef395245b2023-03-13T08:32:24ZrusThe United Institute of Informatics Problems of the National Academy of Sciences of BelarusInformatika1816-03012019-09-01163713841Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM imagesI. E. Starodubtsev0Yu. S. Kharin1M. S. Abramovich2Belarusian State UniversityBelarusian State University; Research Institute for Applied Problems of Mathematics and Informatics of the Belarusian State UniversityBelarusian State University; Research Institute for Applied Problems of Mathematics and Informatics of the Belarusian State UniversityThe method of classification of erythrocytes (red blood cells) based on spectral features of the cell surface images (of physical-mechanical properties maps) obtained with an atomic-force microscope (AFM) is proposed. Each scan line of the original AFM image is considered as a random sequence realization and the discrete Fourier transform is applied to compute its spectral features. The spectral estimates are smoothed on the map and the informative characteristics are computed as the medians of the spectrogram values for each frequency. The classification or two classes of erythrocytes (spherocytes and discocytes) taken from patients with hereditary spherocytosis was carried out by the obtained informative characteristics using the decision trees and boosted decision trees methods. The frequency interval was found with the best classification accuracy – over 82 % for the boosted decision trees method.https://inf.grid.by/jour/article/view/871afm imageserythrocytesmaps of physical-mechanical propertiesmethod of classificationdiscrete fourier transformdecision treesboosted decision trees |
| spellingShingle | I. E. Starodubtsev Yu. S. Kharin M. S. Abramovich Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images Informatika afm images erythrocytes maps of physical-mechanical properties method of classification discrete fourier transform decision trees boosted decision trees |
| title | Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images |
| title_full | Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images |
| title_fullStr | Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images |
| title_full_unstemmed | Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images |
| title_short | Statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces’ AFM images |
| title_sort | statistical classification of erythrocytes in hereditary spherocytosis based on the spectral features of cell surfaces afm images |
| topic | afm images erythrocytes maps of physical-mechanical properties method of classification discrete fourier transform decision trees boosted decision trees |
| url | https://inf.grid.by/jour/article/view/871 |
| work_keys_str_mv | AT iestarodubtsev statisticalclassificationoferythrocytesinhereditaryspherocytosisbasedonthespectralfeaturesofcellsurfacesafmimages AT yuskharin statisticalclassificationoferythrocytesinhereditaryspherocytosisbasedonthespectralfeaturesofcellsurfacesafmimages AT msabramovich statisticalclassificationoferythrocytesinhereditaryspherocytosisbasedonthespectralfeaturesofcellsurfacesafmimages |