Res-Dense Net for 3D Covid Chest CT-scan classification
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 diagnos...
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Zusammenfassung: | 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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DOI: | 10.48550/arxiv.2208.04613 |