COVID-index: A texture-based approach to classifying lung lesions based on CT images.

Pattern Recognition
Vitória de Carvalho BritoAntonio Oseas de Carvalho Filho

Abstract

COVID-19 is an infectious disease caused by a newly discovered type of coronavirus called SARS-CoV-2. Since the discovery of this disease in late 2019, COVID-19 has become a worldwide concern, mainly due to its high degree of contagion. As of April 2021, the number of confirmed cases of COVID-19 reported to the World Health Organization has already exceeded 135 million worldwide, while the number of deaths exceeds 2.9 million. Due to the impacts of the disease, efforts in the literature have intensified in terms of studying approaches aiming to detect COVID-19, with a focus on supporting and facilitating the process of disease diagnosis. This work proposes the application of texture descriptors based on phylogenetic relationships between species to characterize segmented CT volumes, and the subsequent classification of regions into COVID-19, solid lesion or healthy tissue. To evaluate our method, we use images from three different datasets. The results are promising, with an accuracy of 99.93%, a recall of 99.93%, a precision of 99.93%, an F1-score of 99.93%, and an AUC of 0.997. We present a robust, simple, and efficient method that can be easily applied to 2D and/or 3D images without limitations on their dimensionality.

References

Jan 19, 2007·The American Naturalist·Matthew R HelmusAnthony R Ives
Dec 18, 2013·Artificial Intelligence in Medicine·Antonio Oseas de Carvalho FilhoMarcelo Gattass
Mar 13, 2020·Annals of Internal Medicine·Huilan ZhangRonghui Du
Jun 9, 2020·Artificial Intelligence in Medicine·Edson D CarvalhoMarcelo Gattass
Jul 4, 2020·Journal of Biomolecular Structure & Dynamics·Aayush JaiswalManjit Kaur
Oct 9, 2020·Physics in Medicine and Biology·Zhenyu TangDinggang Shen
Apr 8, 2021·Biomedical Signal Processing and Control·Andreia S GaudêncioJoão M Cardoso
Apr 24, 2020·MedRxiv : the Preprint Server for Health Sciences·S. WangBo Xu
Mar 26, 2020·MedRxiv : the Preprint Server for Health Sciences·C. ZhengXinggang Wang
Apr 1, 2020·MedRxiv : the Preprint Server for Health Sciences·A. AbbasM. Gaber

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Software Mentioned

gbtree
MedSeg
DeCoVNet
RF
Sklearn
XGBoost

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