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The analysis of sperm morphology (n = 100) was performed using Vision Sperm automatic sperm analysis system. Evaluation of detection accuracy of sperm morphology was carried out using the following operational criteria that system calculated automatically: diagnostic sensitivity (DSe), diagnostic specificity (DSp) and diagnostic efficiency (DE). The system automatically scanned the slides, identified and performed preliminary sorting (pre-classification) of spermatozoa into four categories of morphological defects: ‘Head’, ‘Neck’, ‘Tail’ and ‘ERC’. Medical validation and generation of report on results of the analysis were carried out simultaneously with scanning of new sperm samples. The average examination time of one glass slide was 3 min 43 sec. The high efficiency of sperm recognition by the Vision Sperm system has been established. Application of Vision Sperm analysis system ensured automation and standardization of assessment a sperm morphology and improved a performance in clinical laboratory.
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Kaznacheeva et al. (2024) studied this question.
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