Computerized Heart and Lung Disease Detection in Low-dose CT Images

Principal Investigator

Name
Pingkun Yan

Degrees
Ph.D.

Institution
Rensselaer Polytechnic Institute

Position Title
Assistant Professor

Email
yanp2@rpi.edu

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-382

Initial CDAS Request Approval
Dec 19, 2017

Title
Computerized Heart and Lung Disease Detection in Low-dose CT Images

Summary
In the proposed project, we will develop deep learning methods for quantification of imaging biomarkers from low-dose CT images for detection disease and cancer related with the heart and lung. The NLST datasets collected from large population of high-risk patients are extremely valuable and will be used for training and validating the developed methods.

Aims

To develop advanced deep learning techniques for improving the imaging information quantification for better association of cancer detection and disease diagnosis through the training on large scale dataset made available by NLST.

Collaborators

Ge Wang, Rensselaer Polytechnic Institute