Washington UniversitySchool of Medicine
Electronic Radiology Laboratory Electronic Radiology Lab banner

Mission & Goals

The Electronic Radiology Laboratory is one of eight research laboratories within the Mallinckrodt Institute of Radiology, Washington University School of Medicine. The Laboratory occupies slightly more than 5000 square feet of office and secure computer room space in the East Imaging Building on the Medical School campus.

ERL was established to investigate digital imaging technologies important to the distributed radiology department of the future, and to enable the responsive delivery of clinical image information to the medical decision-maker. ERL has an international reputation for algorithm and open source software development, especially in the areas of DICOM and IHE communication and testing tools, database and information systems and image reconstruction and processing. We have extensive experience using the Extreme Programming model for software development and in multi-site development projects.

The scope of ERL activities includes image processing in support of clinical research in radiology, and serving as the imaging core for multi-center clinical research projects. Ongoing projects include:

  • A multi-center trial evaluating a transfusion treatment protocol for silent cerebral infarcts in children with sickle cell
  • A multi-institutional study of spiral CT for lung screening
  • The creation and management of a national database of lung CT data
  • CT imaging of the diabetic foot and of cochlear implant electrodes

Tools for image acquisition and de-identification have been developed to support the imaging cores. The lab has worked under contract to the Radiological Society of North America to develop DICOM and IHE tools and to manage international interoperability tests of imaging and IT systems.

Our goal is to continue to push the envelope in applying information technology to medical imaging. The lab maintains a dual focus on: 1) information systems to support clinical and translational research and 2) advancing imaging science in the areas of image analysis, data modeling and information processing.