One of the most contentious areas of research in Medical Image Preprocessing is 3D CT-scan. With the rapid spread of COVID-19, the function of CT-scan in properly and swiftly diagnosing the disease has become critical. It has a positive impact on infection prevention. There are many tasks to diagnose the illness through CT-scan images, include COVID-19. In this paper, we propose a method that using a Stacking Deep Neural Network to detect the Covid 19 through the series of 3D CT-scans images . In our method, we experiment with two backbones are DenseNet 121 and ResNet 101. This method achieves a competitive performance on some evaluation metrics
@article{arxiv.2208.04613,
title = {Res-Dense Net for 3D Covid Chest CT-scan classification},
author = {Quoc-Huy Trinh and Minh-Van Nguyen and Thien-Phuc Nguyen Dinh},
journal= {arXiv preprint arXiv:2208.04613},
year = {2022}
}
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arXiv admin note: text overlap with arXiv:2106.07524 by other authors