Automated Detection of COVID-19 from CT Scans using Convolutional Neural Networks

Rohit Lokwani, Ashrika Gaikwad, Viraj Kulkarni, Anirudha Pant, Amit Kharat

Abstract

COVID-19 is an infectious disease that causes respiratory problems similar to those caused by SARS-CoV (2003). In this paper, we propose a prospective screening tool wherein we use chest CT scans to diagnose the patients for COVID-19 pneumonia. We use a set of open-source images, available as individual CT slices, and full CT scans from a private Indian Hospital to train our model. We build a 2D segmentation model using the U-Net architecture, which gives the output by marking out the region of infection. Our model achieves a sensitivity of 0.96 (95% CI: 0.88-1.00) and a specificity of 0.88 (95% CI: 0.82-0.94). Additionally, we derive a logic for converting our slice-level predictions to scan-level, which helps us reduce the false positives.

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Paper Citation


in Harvard Style

Lokwani R., Gaikwad A., Kulkarni V., Pant A. and Kharat A. (2021). Automated Detection of COVID-19 from CT Scans using Convolutional Neural Networks.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 565-570. DOI: 10.5220/0010293605650570


in Bibtex Style

@conference{icpram21,
author={Rohit Lokwani and Ashrika Gaikwad and Viraj Kulkarni and Anirudha Pant and Amit Kharat},
title={Automated Detection of COVID-19 from CT Scans using Convolutional Neural Networks},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={565-570},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010293605650570},
isbn={978-989-758-486-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Automated Detection of COVID-19 from CT Scans using Convolutional Neural Networks
SN - 978-989-758-486-2
AU - Lokwani R.
AU - Gaikwad A.
AU - Kulkarni V.
AU - Pant A.
AU - Kharat A.
PY - 2021
SP - 565
EP - 570
DO - 10.5220/0010293605650570