Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images.

Pattern Recognition
Chen ZhaoWeihua Zhou

Abstract

This paper aims to develop an automatic method to segment pulmonary parenchyma in chest CT images and analyze texture features from the segmented pulmonary parenchyma regions to assist radiologists in COVID-19 diagnosis. A new segmentation method, which integrates a three-dimensional (3D) V-Net with a shape deformation module implemented using a spatial transform network (STN), was proposed to segment pulmonary parenchyma in chest CT images. The 3D V-Net was adopted to perform an end-to-end lung extraction while the deformation module was utilized to refine the V-Net output according to the prior shape knowledge. The proposed segmentation method was validated against the manual annotation generated by experienced operators. The radiomic features measured from our segmentation results were further analyzed by sophisticated statistical models with high interpretability to discover significant independent features and detect COVID-19 infection. Experimental results demonstrated that compared with the manual annotation, the proposed segmentation method achieved a Dice similarity coefficient of 0.9796, a sensitivity of 0.9840, a specificity of 0.9954, and a mean surface distance error of 0.0318 mm. Furthermore, our COVID-19 classifi...Continue Reading

References

Mar 1, 2005·Psychonomic Bulletin & Review·Scott Glover, Peter Dixon
Sep 13, 2017·Radiographics : a Review Publication of the Radiological Society of North America, Inc·Meghan G LubnerPerry J Pickhardt
Feb 6, 2020·Radiology·Michael ChungHong Shan
Apr 28, 2020·European Journal of Clinical Microbiology & Infectious Diseases : Official Publication of the European Society of Clinical Microbiology·Dilbag SinghManjit Kaur
Jun 17, 2020·Chaos, Solitons, and Fractals·Harsh PanwarVaishnavi Singh
Aug 25, 2020·Measurement : Journal of the International Measurement Confederation·Mohamed LoeyNour Eldeen M Khalifa
Nov 21, 2020·Nature·Bianca Nogrady
Feb 20, 2021·NPJ Digital Medicine·Tahereh JavaheriReza Rawassizadeh

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Software Mentioned

MC
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CovidCTNet
SP
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TensorFlow
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