The imaging and medical informatics research team has expertise in information modeling and management of In Vivo Imaging and constructing medical information systems for research and clinical use. Our mission is to advance information gathering, extracting, storing, processing and presenting in medical imaging areas and related medical information systems for research and clinical use.
In vivo imaging contains vast amounts of information encoded in the pixel data. Extracting observational and computational descriptions of imaging features from pixel data can be done by human or computer program. Storing imaging interpretation results using existing medical lexicons (SNOMED CT, RadLex, privately defined terms, etc.) and well-defined information models permit precise searching and retrieval of stored information. Our team has created Annotation and Image Markup information (AIM) model to captures the semantic meaning of pixel data with user-generated graphical drawings placed on the image and calculations that may or may not be directly related to the drawing in to a single common information source. Our expertise includes but is not limited to DICOM, HL7, Information Modeling, Programming (C#, C++, Java, SQL) and use of National Library of Medicine NLP tools.
Feinberg's research in imagining informatics includes:
- AIM – Supported by National Cancer Informatics Program at the US National Cancer Institute
- DICOM data mining
- Medical Imaging Case Report Forms – the US National Cancer Institute
- Picture Archiving and Communication Systems (PACS) and PACS workstation
- Radiology and Pathology Report Search System
- Radiology Information System
- Transplant Cohort Search System – In Collaboration with Northwestern Transplant Center
Office of Research Administration
Contact the Research Administration and Support staff for assistance with many of the administrative requirements related to research.