Rybalka, A.Kutsenko, A.Megel, Y.Kovalenko, SergiiKovalenko, Svitlana2023-02-092023-02-092022Rybalka A. Methods for Medical Images Contrast Measuring and Enhancement to Improve the Accuracy of Pathology Detection / A. Kutsenko, Y. Megel, S. Kovalenko, S. Kovalenko, D. Pelikh, A. Rybalka // XXXII International Scientific Symposium Metrology and Metrology Assurance (MMA), 7-9 september 2022. – Sozopol, Bulgaria, 2022. – P. 1-6.https://openarchive.nure.ua/handle/document/21743The article describes the process of developing software for enhancing the contrast of radiographs and comparing the impact of these methods on the accuracy of determining the pathology. The paper provides an overview and analysis of the use of artificial neural networks in various fields of medicine. This research describes and implements contrast enhancement methods, such as: image contrast enhancement method using entropy, image contrast enhancement method using standard deviations of local neighborhood element brightness values, local contrast non-linear transformation method, image contrast enhancement method using statistical determination of local contrasts, method using the standard deviation of the intensities of the elements of the local neighborhood of the image. The results of the methods were compared using data analysis. As a result, software was developed to enhance image contrast and train the neural network of the VGG16 architecture.enmedicinediagnosticsradiographdigital image processingConference proceedings