The quantitative analysis of Pneumoconiosis
Principal Investigator
Name
Xiaoyu Li
Degrees
PhD
Institution
University of Electronic Science and Technology of China
Position Title
Associate Professor
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-153
Initial CDAS Request Approval
Aug 31, 2015
Title
The quantitative analysis of Pneumoconiosis
Summary
Pneumoconiosis is a disabling disease with diffusely distributed fibrosis in lung tissues. Opacities with specific shapes present in computed tomography images. In the advanced stages of the disease, the opacities are mainly small lung nodules. The analysis of this kind of nodules is our study point. With the development of the CT scanning technique and 3D image reconstruction, the brightness of nodules and normal lung tissues diverse obviously. Consequently, the quantitative imaging analysis of pneumoconiosis lesions is made possible. We proposed to quantitative analyze the nodules with machine learning methods. Designing and implementing a preliminary automatic counting system is our ultimate goal.
Aims
1. Develop a method for automatic nodules segmentation.
2. Search for suitable textural and morphologic characteristics, including 3D characteristics, for automatic nodules decision.
3. Implement a system for automatic counting of nodules.