Joseph Reinhardt, Ph.D

Affiliations: Associate Professor, Department of Biomedical Engineering; Image Analysis Group Leader, Iowa Institute for Biomedical Imaging
Area: Biomedical Engineering

 

Joseph M. Reinhardt, PhD, is an Associate Professor of Biomedical Engineering at the University of Iowa.  He received his BS degree from Carnegie Mellon University in 1985, MS degree from Northeastern University in 1988, and PhD degree from Penn State University in 1994, all in Electrical Engineering.  From 1985 to 1990, he worked as an engineer in industry. After finishing his PhD, he came to Iowa as a post-doctoral fellow in the Radiology  Department.  In 1996 he became an Assistant Research Scientist in the Radiology Department.  He joined the College of Engineering as an Assistant Professor in 1997.

 

One of Dr. Reinhardt's main research projects uses 3D CT imaging to study normal and abnormal lung biomechanics.  In a collaborative project with Drs. Eric Hoffman, Geoffrey McLennan,  Gary Christensen, and Madhavan Raghavan,  the group uses 3D nonlinear image registration to match lung CT images acquired at different levels of inflation. After image registration, post-processing yields a map of lung tissue expansion and tissue strain, which can be   used to characterize the normal lung and   detect biomechanical changes in subjects    with emphysema, lung cancer, and other       lung diseases.  See image at right.

 

 

A local start-up company, VIDA Diagnostics,  was founded by Drs. Reinhardt, Hoffman, McLennan, and Sonka to commercialize software tools for quantitative lung image analysis.  VIDA is located at the University          of Iowa business incubator. See image at right.

 

 

 

 

 

 

Dr. Reinhardt works with opthalmologist Dr. Michael Abramoff and post-doctoral fellow Dr. Sangyeol Lee to develop image analysis and registration methods for fundus camera imaging of the eye.  Fundus camera imaging can detect important signs of eye diseases such as glaucoma, diabetic retinopathy, and macular degeneration, but the camera is only able to image a small portion of the retina. Reinhardt, Abramoff, and Lee have developed a novel image registration process that stitches together several fundus camera images into a geometrically correct image mosaic with a much larger view of the retina.  They are now using these image mosaics within a computer-aided detection system to automatically identify signs of eye disease.  See image at right.