Lung Nodule Malignancy Classification Based On Time-Series Model
Principal Investigator
Name
Chaoran Jia
Degrees
graduate student
Institution
Dalian University of Technology
Position Title
None
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-969
Initial CDAS Request Approval
Oct 18, 2022
Title
Lung Nodule Malignancy Classification Based On Time-Series Model
Summary
We investigate time series of medical images to diagnose the severity of lung CT images through multiple time points and combine these time points for classification, segmentation or prediction tasks.
Aims
The goal of our research is to design a model capable of processing time-series images so that the model can derive key information from the changes and development of pulmonary nodules in the same patient before and after several times to determine the period in which they are located and possibly perform classification, segmentation or prediction tasks.
Collaborators
Liang Zhao, Dalian University of Technology
Yu Shao, Dalian University of Technology
Chaoran Jia, Dalian University of Technology
Zhuo Liu, The First Affiliated Hospital of Dalian Medical University