Skip to Main Content

COVID-19 is an emerging, rapidly evolving situation.

What people with cancer should know: https://www.cancer.gov/coronavirus

Get the latest public health information from CDC: https://www.coronavirus.gov

Get the latest research information from NIH: https://www.nih.gov/coronavirus

Principal Investigator
Name
Yufa Xia
Degrees
M.D.
Institution
Shenzhen institutes of advanced technology, Chinese Academy of Sciences
Position Title
Research assitant
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-578
Initial CDAS Request Approval
Nov 4, 2019
Title
Chest CT image registration
Summary
Image registration is a crucial and fundamental procedure in Image Guided Radiation Therapy (IGRT). We aim to develop a deep learning-based algorithm for deformable medical image registration for IGRT. We would like to take advantage of large scale public datasets from different organizations to train and test the presented deep learning-based deformable registration algorithm. Moreover, we wish to develop a robust deformable registration algorithm that can perform well on generic data. The demographic data from the report could be used to obtain more information about the population distribution, which could be used in our further analysis.
Aims

1. Develop a learning-based algorithm for deformable medical image registration.
2. Using different datasets to accomplish cross-validation on deep learning with the help of demographic data.

Collaborators

Zhihe Zhao, Shenzhen institutes of advanced technology, Chinese Academy of Sciences.
Jiarui Zhu, Shenzhen institutes of advanced technology, Chinese Academy of Sciences.