Application of mathematical model of logistic regression for malignant skin lesions recognition on digital skin images
Abstract
Application of mathematical model of logistic regression for malignant skin lesions recognition on digital skin images
Incoming article date: 25.08.2021The aim of this study was to analyze the possibility of using a mathematical model of logistic regression for the recognition of malignant neoplasms on digital images of the skin. The study used a database containing 6594 digital skin images. At the first stage of the study, digital skin images were segmented to isolate the object under study, in which morphometric and color characteristics corresponding to the parameters of the classical ABCD system were determined. At the second stage, the characteristics were used in the classification into malignant and benign neoplasms using logistic regression. When classifying images, the highest value of the accuracy indicator (67.9 [66.9; 68.8]%) was obtained during classification using logistic regression, built on the basis of the reverse Wald stepwise method. Thus, the logistic regression built on the basis of the reverse stepwise Wald method can be applied in the classification of malignant neoplasms on digital images of the skin, but further research and determination of the optimal parameters are required.
Keywords: mathematical model, digital skin images, logistic regression, image classification, skin cancer