Development and validation of AI-based lung nodule management and lung analysis software
Principal Investigator
Name
Hee Jun Park
Degrees
M.S.
Institution
CORELINESOFT
Position Title
General manager
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-623
Initial CDAS Request Approval
Dec 26, 2019
Title
Development and validation of AI-based lung nodule management and lung analysis software
Summary
Many studies have shown that AI-based lung nodule CAD plays an important role as a secondary reader. And we are developing a software for management of pulmonary nodules through detection, segmentation and analysis. So the first purpose of this project is to detect lung nodules, and the second is to manage detected lung nodules.
In addition to lung nodule management, we are going to verify and improve lung lobes, airway and vessel segmentation performance for lung analysis software. We have already completed verification after developing the lung analysis software, but we hope to get more robust analyzed results on various vendors, kernel and dose by using this data.
Aims
- Development and validation of the lung nodule detection with high sensitivity and low false positive
- Measurement of the size and volume of detected lung nodules and management of the volume and characteristics changes of lung nodules based on f/u scan
- Enhancement and validation of segmentation performance of the lobes, airway and vessel for lung analysis
Collaborators
None