Detection and classification of clusters of microcalcifications on mammographic images.

Autor:	Pasynkov, D. V., Egoshin, I. A., Kolchev, A. A., Romanycheva, E. A., Klyushkin, I. V., Pasynkova, O. O.
Předmět:	RESEARCH funding BREAST tumors RESEARCH evaluation CALCINOSIS DESCRIPTIVE statistics DIAGNOSTIC errors DECISION making in clinical medicine MAMMOGRAMS DIGITAL image processing DECISION trees SENSITIVITY & specificity (Statistics)
Zdroj:	Biomedical Engineering; May2024, Vol. 58 Issue 1, p40-44, 5p
Abstrakt:	An algorithm for detecting and classifying clusters of microcalcifications on mammograms is proposed. A feature of the algorithm proposed here is its potential for application to different types of calcifications and clusters of calcifications (both benign and suspicious). At the same time, vascular calcifications, which often give false positive results in algorithms, are analyzed separately, and a solution to this problem is proposed. The effectiveness of the proposed methods was assessed using a database of mammograms from patients with verified diagnoses. The classification algorithm achieved 96.15% accuracy, 95.32% specificity, and 98.21% sensitivity. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
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