Development of CAD for lung nodule screening
Principal Investigator
Name
Naïm Jalal
Degrees
Ph.D
Institution
GE HEALTHCARE
Position Title
Sr Technical Project Manager
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-977
Initial CDAS Request Approval
Oct 27, 2022
Title
Development of CAD for lung nodule screening
Summary
Lung cancer is classified as a cancer with poor prognosis because it is most often diagnosed at a late stage. There is a growing popularity of implementing screening programs. The screening examination is a low-dose chest CT without injection. Therefore, the volume of chest CT images increases rapidly. In order to support radiologists in the overload of work, it is necessary to develop tools to support them.
This project aims to develop algorithms to detect and segment lung nodules on CT imaging using machine learning. The NLST database will be used for the development/validation of these algorithms.
This project aims to develop algorithms to detect and segment lung nodules on CT imaging using machine learning. The NLST database will be used for the development/validation of these algorithms.
Aims
Create algorithms to detect and segment lung nodules on low dose CT.
Collaborators
N/A