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Cell
Tracking for Tissue Engineering
Head: Takeo
Kanade, Lee E.
Weiss and Phil G.
Campbell
Contact: Kang Li (kangli@cs.cmu.edu)
Mailing
address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Associated
center: MRTC
Associated lab/group: Tissue
Engineering
Biological engineering applies knowledge about genomics, proteomics, and cellomics to develop new diagnostics and therapeutics for medicine. The high cost and long timelines for gathering and interpreting experimental data is a barrier to efficient exploration of the complex and high-dimensional design spaces of biological-based application systems. To overcome this barrier, researchers are relying more-and-more on high-throughput micro-array technologies to simultaneously conduct hundreds to thousands of individual experiments on a single test chip. However, studying cell responses to micro-array environments (cellomics) has been limited to either single endpoint measurements or tracking a relatively few, sparsely spaced cells over time.
We are developing fully-automated computer vision-based cell tracking algorithms and system that overcomes these limitations. The system will track whole populations of cells on a test chip in real-time (i.e., image analysis be completed for each frame prior to next frame, with images typically taken at intervals of 5 to 10 minutes), not only so that results will be immediately available, but so that experiments can even be modified or terminated based on real-time feedback. This system will be capable of automatically determining the spatiotemporal history of dense populations of cells over extended period of times (days to weeks), and will help to revolutionize high-throughput discovery.Note: This list may not be comprehensive. It contains only those publications in the RI publications database. Entries are listed in reverse chronological order.