Effectiveness assessing of softwares with AI for chest area x-ray images post-processing

Abstract

Diagnostic radiology is a branch of medicine describes of ionizing radiation using to study the structure and functions of normal and pathological altered human organs and systems for the prevention and detection of diseases. X-ray irradiation is the most common diagnostic method in Radiology and it makes possible to identify and diagnose diseases and injuries for further treatment of patients. In particular, development of artificial intelligence (AI) has led the creation of different software for X-ray images processing to improve pathologists recognition by operator. At this moment there are lots of means and methods have been developed by different software engineers to find out “the perfect solution” for this problem. Respiratory diseases occupy one of the leading places in Ukraine. The main share of pathologies is acute viral infections, bronchitis, pneumonia and tuberculosis. In one year, about 15.5 million chest X-ray studies perform in Ukraine only for tuberculosis detection. It was the reason to select chest X-ray studies for processing's effectiveness assessing. For effectiveness assessing we have made quantitative contrast measurements for selected areas on original and processed chest X-ray images.

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