COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer

Autor: Jiang, Juntao, Lin, Shuyi
Rok vydání: 2021
Předmět:
Druh dokumentu: Working Paper
Popis: The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damage. Chest X-ray images are widely used for COVID-19 diagnosis and the Artificial Intelligence method can increase efficiency and accuracy. In the Challenge of Chest XR COVID-19 detection in Ethics and Explainability for Responsible Data Science (EE-RDS) conference 2021, we proposed a method that combined Swin Transformer and Transformer in Transformer to classify chest X-ray images as three classes: COVID-19, Pneumonia, and Normal (healthy) and achieved 0.9475 accuracies on the test set.
Databáze: arXiv