ALGORITHMS FOR RECOGNITION OF HISTOLOGICAL IMAGES BASED ON THRESHOLD RULES
Keywords:
Histological image, threshold rules, features of objects, recognition operator, models based on threshold rulesAbstract
The article discusses various histological image recognition algorithms to improve the accuracy of pathology diagnostics. Particular attention is paid to the proposed threshold rule-based method, which demonstrates higher classification accuracy and training speed compared to popular machine learning methods such as SVM, Random Forest, and XGBoost. During the experiments, the proposed method showed high accuracy with minimal training and classification time. The results of a comparative analysis by key metrics are presented, confirming the effectiveness of the proposed approach for automating diagnostics in digital pathology.
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