Decision support system in radiology for fast diagnostics of thoracic diseases under COVID-19 pandemic conditions
Автор: Borodyansky I.M.
Журнал: Cardiometry @cardiometry
Рубрика: Short report
Статья в выпуске: 21, 2022 года.
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In the present article the relevance of using DSS under the current conditions for image recognition and, as a more specific application, for the purpose of additional assistance rendered to medical experts (radiologists) in their decision-making and preparing findings upon assessment of X-ray images is considered. The paper analyzes the requirements for some expert DSS and their main characteristics that they should have; considered and selected is the necessary software for making rapid diagnoses of diseases of the thorax. All these modern requirements and characteristics are met by the Deep Learning Studio (DLS) software, which allows using deep convolutional neural network Inception V3 to teach this network and further obtain optimal results in the recognition and diagnosis of diseases of the thorax by assessing X-ray images. As a result of this study, a ready-made DSS intended for use by medical institutions for additional assistance to radiologists to prepare findings according to X-ray images has been obtained.
Dss, dls, transfer learning, inception v3 neural network, x-ray images, pneumonia, myocarditis
Короткий адрес: https://sciup.org/148324179
IDR: 148324179
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