ABOUT THE INFLUENCE OF THE QUALITY OF DATABASES OF X-RAY IMAGES OF TUBERCULOSIS PATIENTS ON DISEASE DIAGNOSIS
A.V. Karpov1, V.I. Kozik2, E.S. Nejevenko2, Y.Sh. Schwartz1
1Federal State Budgetary Institution "Novosibirsk TB Research Institute", Ministry of Health of the Russian Federation, Novosibirsk, Russia
2Institute of Automation and Electrometry, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
Keywords: tuberculosis, x-ray picture, convolutional neural networks, diagnosis, training sets
Abstract
The article explores the reliability of training samples used to train convolutional neural networks for the diagnosis of pulmonary diseases. It is shown that the sample, in which 3500 X-ray pictures of healthy patients and the same number of pictures of patients with tuberculosis, is very heterogeneous. When training on different parts of the sample and recognizing its various parts, significantly different results are obtained.
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