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[Lab image] Tissue Engineering
Head: Lee Weiss

Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

Associated center: MRTC

For more information, see this lab's homepage.

This page last updated - January 1999.
Jump to: Lab Description | Personnel | Projects | Publications

Lab Description

Tissue Engineering is a multidisciplinary field that applies the principles of biology and engineering to develop tissue substitutes to restore, maintain, or improve the function of diseased or damaged human tissues. One approach for engineering tissue involves seeding biodegradable scaffolds with donor cells and/or growth factors, then culturing and implanting the scaffolds to induce and direct the growth of new, healthy tissue.

The need for bone substitutes is particularly important. Bone substitutes are often required to help repair or replace damaged or diseased tissues in cases ranging from trauma, to congenital and degenerative diseases, to cancer, to cosmetics. Our vision for creating tissue engineered bone is an advanced CAD/CAM (computer-aided-design/computer-aided-manufacturing) bioreactor system capable of growing large-scale, customized bone substitutes as depicted in the figure above. Our current research involves not only laying the foundation for several of the components required for realizing such an advanced system, but also gaining knowledge and developing components that will have clinical relevance in the nearer term.

Personnel [Past members]

Name Title Email Address
Phil Campbell Visiting Research Scientist
Kaigham Gabriel Distinguished Service Professor, RI/ECE kgabriel@cs.cmu.edu
Prashant Kumta Associate Professor, MSE kumta+@cmu.edu
Kang's personal homepage Kang Li PhD Student, ECE kangl@cmu.edu
Eric Miller PhD Student, Bio Med edmiller@andrew.cmu.edu
Mark Mooney Associate Professor
Lawrence Schultz Senior Research Engineer schultz+@cs.cmu.edu
John Wahlig, M.D.

Current Projects

Cell Tracking - We are developing fully-automated computer vision-based cell tracking algorithms and a system that automatically determines the spatiotemporal history of dense populations of cells over extended period of time.
 

Recent publications [View all 17 publications]


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