Using Algorithms to Produce High Content Information from Cell and Tissue Images

Thursday, November 17, 2011 - 11:30am - 12:30pm
Keller 3-180
Jens Rittscher (General Electric)
While the chemical structure of DNA is well understood, determining how genome-encoded components function in an integrated manner to perform cellular and organismal function is still an open challenge. The talk will motivate that imaging, more specifically the extraction of quantitative information, plays a critical role in this process. Such measurements will enable the automatic monitoring of cellular and intracellular events, and providing information about specific molecular mechanisms in individual cells.

By providing some specific examples it will be illustrated how specific computer vision algorithms enable the analysis of data sets and complex biological specimens that cannot be analyzed through manual inspection. The talk will highlight specific examples on how image analysis algorithms can be used to extract high content data. Specifically I will show how image segmentation methods are used to extract protein expression information in a novel sequential multiplexing process GE developed. In addition it will be discussed how statistical shape analysis methods can be applied to assess cellular morphology as well as the structure of entire organisms. Finally, it will be shown how the analysis of apparent motion can be used to monitor cardiomyocyte populations.

While imaging data potentially has much to add to models for systems biology, the usefulness of imaging information is dependent on the quantitative nature of the data and other aspects of its quality. Developing an awareness of the important long-term factors and challenge will help ensure acceptance of image analysis methods. Today image analysis methods are already used to study complex biological processes.