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arXiv · 2208.04613

Res-Dense Net for 3D Covid Chest CT-scan classification

Quoc-Huy Trinh·Minh-Van Nguyen·Thien-Phuc Nguyen Dinh
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Abstract

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

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Quoc-Huy Trinh, Minh-Van Nguyen, Thien-Phuc Nguyen Dinh. 2022-08-09. Res-Dense Net for 3D Covid Chest CT-scan classification. https://arxiv.org/abs/2208.04613

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