论文标题
3D共同胸部CT-SCAN分类的RES密集网
Res-Dense Net for 3D Covid Chest CT-scan classification
论文作者
论文摘要
医学图像预处理中最有争议的研究领域之一是3D CT扫描。随着Covid-19的迅速传播，CT扫描在正确，迅速诊断疾病的功能变得至关重要。它对预防感染有积极影响。通过CT-Scan图像诊断疾病有许多任务，包括Covid-19。在本文中，我们提出了一种使用堆叠深神经网络的方法，通过一系列3D CT-SCANS图像来检测COVID 19。在我们的方法中，我们使用两个骨架的实验是Densenet 121和Resnet 101。此方法在某些评估指标上实现了竞争性能
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
