This project will determine improved rapid and motion resilient MR approaches for deep learning-based generation of substitute CT images, enabling greater quantitative accuracy and robustness for PET/MR and MR-only radiation treatment planning.
Improved Techniques for Substitute CT Generation from MRI Datasets
The PI of this project is: Alan B McMillan, PhD
This project is funded by: NIH
The term of this project is: January 2019 to January 2022
The number of subjects scanned during this project is: 260