Technology Development of Deep Learning based Lung CT and Chest X-Ray Reading

Principal Investigator

Name: Jing Xiao
Degrees: Ph.D
Institution: Ping An Technology(Shenzhen) Company Ltd.
Position Title: The Chief Scientist and Dean of Technology Research Institute
Email: xiaojing661@pingan.com.cn

Project Information
Study: NLST
Project ID: NLST-345
Title: Technology Development of Deep Learning based Lung CT and Chest X-Ray Reading

Summary

Chest X-ray and Lung CT remain two of the major clinical diagnosis modalities for various lung diseases, such as lung nodule, interstitial lung diseases, hypoinflation, pneumothorax, cardiomegaly, etc. Usually, X-ray imaging is often the first imaging diagnosis tool which applies to large population for preventative care, Lung CT imaging is the more precise tool for diagnosing. Our research aim to make use of both Chest X Ray and Lung CT to help diagnosis of diseases in early stages, or give reliable assessment on the risk of disease, based on which therapies or prevention measures could be targeted. In this way, the effect of medical measures could be maximized with minimum resources. It could provide a more accurate approach for disease prevention. Firstly, it could identify the individuals that have higher risk of disease and require prevention measures. Secondly, it could help clinicians to select appropriate prevention methods based on the person’s condition. The research thrust in comprehensive chest X-ray and lung CT image understanding can potentially grow into a widely accepted lung imaging prescreening tool.

Aims

To improve and develop scalable deep learning empowered technical solutions to detect or tag major diseases from chest X-ray and lung CT images in high precision
Collaborators

Le Lu, National Institutes of Health Clinical Center (NIHCC)