Section 80
Chapter 79,347

Object or Background: An Interpretable Deep Learning Model for COVID-19 Detection from CT-Scan Images

Singh, G.; Yow, K.-C.

Diagnostics 11(9)


ISSN/ISBN: 2075-4418
PMID: 34574073
Accession: 079346796

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The new strains of the pandemic COVID-19 are still looming. It is important to develop multiple approaches for timely and accurate detection of COVID-19 and its variants. Deep learning techniques are well proved for their efficiency in providing solutions to many social and economic problems. However, the transparency of the reasoning process of a deep learning model related to a high stake decision is a necessity. In this work, we propose an interpretable deep learning model Ps-ProtoPNet to detect COVID-19 from the medical images. Ps-ProtoPNet classifies the images by recognizing the objects rather than their background in the images. We demonstrate our model on the dataset of the chest CT-scan images. The highest accuracy that our model achieves is 99.29%.

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