The Image Processing
and Informatics Laboratory (IPI) is located at 1042 Downey Way. Denney Research Center (DRB) 264, Los Angeles, CA 90089-1111
Our research facility includes
PACS Simulator, Fault-tolerance Server, Data Grid, PACS workstations,
CAD servers, and connections to two clinical PACS.
Reseach topics include:
- Computer Aided Detection and Diagnosis
- Data Grid and Image Archival
- Imaging Informatics Technology
- PDA Application in Clinical Environment
- Radiation Therapy Informatics
- Clinical Workflow Model
- CAD - PACS Integration Toolkit
- EPR for a surgical environment
- Multimedia ePR for Rehabilitation
- eFolder for Multiple Sclerosis Decision Support
- Spinal Cord Injury Pain Classification
New IPILab website URL
July 20th, 2017
IPILab has officially moved its website to the new URL at:
Please update your bookmarks. Look forward to more website updates in the future!
IPILAB UPDATE: Congratulations to Dr. Ximing Wang!
March 7th, 2017
Congratulations to Dr. Ximing Wang! He just passed his Ph.D. defense in Biomedical Engineering, USC on March 2nd, 2017, with his PhD dissertation, “An Intelligent Workflow Engine Informatics System (IWEIS) with Knowledge Discovery Tools for Imaging-Based Clinical Trials”, which is a critical breakthrough in the imaging informatics field.
IPILab has moved to USC Park Campus
October 16th, 2014
We have moved from our previous location in Annenberg Research Park to within the Department of Biomedical Engineering on the USC University Park Campus, in the Denney Research Center Building. Our new location helps to create a more convenient research and learning environment, which encourages more collaborations and sharing of ideas with other research groups in our BME department. We welcome you to visit our new laboratory and offices at:
Denney Research Center (DRB) 264
1042 Downey Way
Los Angeles, CA 90089-1111
IPILab Update: RSNA 2013
August 20th, 2013
The IPILab have 4 abstracts accepted to RSNA (Radiological Society of North America) 2013.
The list is as follows:
Web-based DICOM-SR Viewer for CAD data of multiple sclerosis lesions in an imaging informatics-based eFolder
Authors: Brent Liu, Kevin Ma, Jeff Zhang
An open source, rich-client web application for visualizing DICOM RT data
Authors: Brent J. Liu, Ruchi R. Deshpande, David Clunie, John DeMarco, Jorge Documet
Web-based neurological pain classifier tool utilizing Bayesian decision theory for pain classification in spinal cord injury patients.
Authors: Sneha K. Verma, Sophia Chun, Brent J. Liu
An imaging informatics-based system with a novel intelligent workflow engine to support rehabilitation clinical trial research
Authors: Brent Liu, Ximing Wang, Clarisa Martinez, Carolee Winstein
We would appreciate your interests in our topics.