Impact of Chest X-ray Images Enhancement to COVID-19 Classification Using Vector Quantization and Fuzzy S-tree

The chest X-ray (CXR) is a cheap and accurate method for lung-related disease diagnosis. The paper focuses on the COVID-19 detection in CXR images using the fuzzy medical image retrieval (FMIR) approach. Medical images often suffer from unbalanced brightness and low contrast, which reduce their readability. Therefore, an enhancement method is applied here to obtain a wider dynamic range of intensities and improve the visibility of details. The experiments test various parameters settings of the FMIR and compare the classification performance of the FMIR applied to original and enhanced images. The results show that the enhancement slightly improves the sensitivity, specificity and accuracy of the proposed method.

Automated summary

The chest X-ray is a cost-effective and accurate method for diagnosing lung-related diseases. This paper focuses on using the fuzzy medical image retrieval approach for COVID-19 detection in CXR images. By applying an enhancement method, the visibility of details is improved and the sensitivity, specificity, and accuracy of the proposed method are slightly enhanced.