The purpose of the registry/repository is to provide a mechanism to store data and images to help facilitate the development of a deep learning framework for automatic, objective, fast, and accurate image quality assessment (IQA) of structural MRI data. IQA is typically performed via visual inspection by MRI technologists and can be time-consuming, subjective, and error prone. Our method will complete IQA in milliseconds with high sensitivity and specificity.
Thank you for your interest, but this study is recruiting by invitation only.
United States (Nationwide)
Pew-Thian Yap
Radiology - Research
Clinical or Medical
Registry
Healthy Volunteer or General Population
24-1073
Copyright © 2013-2022 The NC TraCS Institute, the integrated home of the NIH Clinical and Translational Science Awards (CTSA) Program at UNC-CH. This website is made possible by CTSA Grant UL1TR002489 and the National Center for Advancing Translational Sciences.
Questions?
