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This paper presents our solution for the first challenge of the 3rd Covid-19competition, which is part of the "AI-enabled Medical Image Analysis Workshop"organized by IEEE International Conference on Acoustic, Speech and SignalProcessing (ICASSP) 2023. Our proposed solution is based on a Resnet as abackbone network with the addition of attention mechanisms. The Resnet providesan effective feature extractor for the classification task, while the attentionmechanisms improve the model's ability to focus on important regions ofinterest within the images. We conducted extensive experiments on the provideddataset and achieved promising results. Our proposed approach has the potentialto assist in the accurate diagnosis of Covid-19 from chest computed tomographyimages, which can aid in the early detection and management of the disease.

UniCT DMI Solution for 3rd COV19D Competition on COVID-19 Detection through attention-based CNN for CT Scan