FIELD: medicine; computer engineering.
SUBSTANCE: invention relates to computer engineering and medicine. Image containing blood cells is obtained; method includes detecting, on the obtained image, blood cells; distinguished are normal and peripheral blood cells; isolating normal blood cells and cutting them from the image, and blood boundary cells are excluded from further analysis; followed by classification of blood cells by types, wherein: obtaining for each image of cut blood cells using augmentation method, which consists in obtaining from a single image a set of images, by turns, images and cuts of part of image; method includes analysing a set of images obtained for each cell and classifying each blood cell by type according to the given set.
EFFECT: technical result consists in automatic detection and classification of blood cell types using deep convolutional neural networks.
5 cl, 1 tbl, 7 dwg
| Title | Year | Author | Number |
|---|---|---|---|
| METHOD FOR DIFFERENTIAL DIAGNOSIS OF CROHN'S DISEASE OR ULCERATIVE COLITIS | 2021 |
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| INTELLIGENT SPACE SYSTEM FOR MONITORING BUILDINGS AND STRUCTURES | 2018 |
|
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| METHODS FOR TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS BASED ON DEEP LEARNING | 2018 |
|
RU2767337C2 |
| SPLICING SITES CLASSIFICATION BASED ON DEEP LEARNING | 2018 |
|
RU2780442C2 |
| SYSTEMS AND METHODS OF ASSESSING THE VIABILITY OF EMBRYOS | 2018 |
|
RU2800079C2 |
| METHOD FOR PROVIDING COMPUTER VISION | 2022 |
|
RU2791587C1 |
