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COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI System (2403.06242v2)

Published 10 Mar 2024 in eess.IV and cs.CV

Abstract: Computer-aided diagnosis (CAD) systems stand out as potent aids for physicians in identifying the novel Coronavirus Disease 2019 (COVID-19) through medical imaging modalities. In this paper, we showcase the integration and reliable and fast deployment of a state-of-the-art AI system designed to automatically analyze CT images, offering infection probability for the swift detection of COVID-19. The suggested system, comprising both classification and segmentation components, is anticipated to reduce physicians' detection time and enhance the overall efficiency of COVID-19 detection. We successfully surmounted various challenges, such as data discrepancy and anonymisation, testing the time-effectiveness of the model, and data security, enabling reliable and scalable deployment of the system on both cloud and edge environments. Additionally, our AI system assigns a probability of infection to each 3D CT scan and enhances explainability through anchor set similarity, facilitating timely confirmation and segregation of infected patients by physicians.

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Authors (5)
  1. Demetris Gerogiannis (1 paper)
  2. Anastasios Arsenos (11 papers)
  3. Dimitrios Kollias (48 papers)
  4. Dimitris Nikitopoulos (1 paper)
  5. Stefanos Kollias (26 papers)
Citations (16)
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