RT Impact: Indiana University
IU School of Medicine Center for NeuroImaging (CfN)
CfN enlisted the help of RT to develop Scalable Quality Assurance for Neuroimaging (SQAN), a quality control service to improve PET-based research. Mistakes are difficult for researchers to spot using existing data extraction methods, which can affect the quality of a study’s data. In response, the Scalable Compute Archive (SCA) team developed SQAN.
“Partnering with SCA, we are using SQAN to better understand the timing of the different acquisitions, and we can go back and retroactively apply that data to our data processing stream.” – Dr. Karmen Yoder, professor of radiology and imaging sciences
ConnPipe combines state-of-the-art tools from various image processing packages along with algorithms developed in-house to process complex datasets within one coherent framework. The collaboration of SCA, CfN, and IU School of Medicine researchers has allowed ConnPipe to be significantly improved, allowing the team to make the pipeline faster and more efficient, more modular and adaptable to new techniques, while allowing for better utilization of IU’s vast supercomputing resources.
“Research of this nature helps to uncover reliable indicators of impairment, which may provide evidence toward previously undiscovered causal biological and physiological mechanisms underlying the nature of treatment and its side effects.” – Meichen Yu, postdoctoral researcher, CfN
The Scalable Compute Archive took on the management of XNAT, an open-source imaging informatics platform supporting research by the Center for NeuroImaging (CfN) at the IU School of Medicine. The migration involved critical upgrades, including the ability to run the program virtually on a web browser.
“XNAT is an enabling technology for our advanced neuroimaging and -omics research on Alzheimer’s disease and related brain disorders. The ability of our IT group to work hand in hand with the SCA greatly facilitates progress.” – Dr. Andrew Saykin, director, CfN and IADRC