Tag Archives: Imaging Analytics

Case Study: Mount Sinai School Of Medicine

XNAT pipelines are the perfect tool for generating high resolution connectomes – detailed maps of brain networks in individual patients.
Dan Marcus, President, Radiologics

The Translational and Molecular Imaging Institute at Mount Sinai School of Medicine is developing new neuroimaging methods to diagnose and guide treatment in a range of psychiatric disorders. XNAT serves as the central analytic engine for all patient scans collected at the Institute.

Radiologics worked with Dr. Gordon Xu, assistant professor of radiology at Mount Sinai. XNAT pipelines are used to process incoming scans, including anatomic images, resting state fMRI, and diffusion tensor imaging.

Mt Sinai has been particularly impressed with XNAT  integration with the Institute’s scanners. With XNAT’s DICOM workflow, transferring data from scanners is as simple as sending to a PACS but with the benefit of user access control, web-based access, and advanced imaging analytics.

At Mount Sinai, XNAT imaging analytics are driving psychiatric research.