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

arXiv: https://arxiv.org/abs/2208.04613 · HTML: https://mlsanity.com/paper/2208.04613/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 23 references that are in the map.
- First posted on arXiv 9 Aug 2022.

## Builds on (most cited first, 13 of 13)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Xception: Deep Learning with Depthwise Separable Convolutions](https://mlsanity.com/paper/1610.02357/) (2016)
- [Deep Transparent Prediction through Latent Representation Analysis](https://mlsanity.com/paper/2009.07044/) (2020)
- [MIA-COV19D: COVID-19 Detection through 3-D Chest CT Image Analysis](https://mlsanity.com/paper/2106.07524/) (2021)
- [Macro F1 and Macro F1](https://mlsanity.com/paper/1911.03347/) (2019)
- [COVID-VIT: Classification of COVID-19 from CT chest images based on vision transformer models](https://mlsanity.com/paper/2107.01682/) (2021)
- [Diagnosing COVID-19 Pneumonia from X-Ray and CT Images using Deep Learning and Transfer Learning Algorithms](https://mlsanity.com/paper/2004.00038/) (2020)
- [A 3D CNN Network with BERT For Automatic COVID-19 Diagnosis From CT-Scan Images](https://mlsanity.com/paper/2106.14403/) (2021)
- [A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans](https://mlsanity.com/paper/2005.10992/) (2020)
- [Classification of COVID-19 in CT Scans using Multi-Source Transfer Learning](https://mlsanity.com/paper/2009.10474/) (2020)
- [COVID Detection in Chest CTs: Improving the Baseline on COV19-CT-DB](https://mlsanity.com/paper/2107.04808/) (2021)
- [TeliNet: Classifying CT scan images for COVID-19 diagnosis](https://mlsanity.com/paper/2107.04930/) (2021)
- [3D RegNet: Deep Learning Model for COVID-19 Diagnosis on Chest CT Image](https://mlsanity.com/paper/2107.04055/) (2021)

## Abstract (arXiv)

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