Spatiotemporal Contour Tracking of Microtubules
M. A. El Saban and B. S. Manjunath
Electrical and Computer Engineering Department, University of California, Santa Barbara
{msaban, manj} [at] ece.ucsb.edu
Electrical and Computer Engineering Department, University of California, Santa Barbara
{msaban, manj} [at] ece.ucsb.edu
Abstract
Microtubules (MTs), one of three major cytoskeletal components, serve numerous critical functions in cells. Mechanistically, MTs are not static polymers; rather, they can be very dynamic and their precise patterns of growing and shortening behaviors are critical to their many functions. Among the challenges confronting modern molecular cell biology is to accurately and thoroughly quantify the dynamic behaviors of cellular MTs under a variety of experimental conditions. MTs in living cells are generally visualized by time-lapse fluorescence microscopy. They appear as thin, hair-like structures, a subset of which are actively changing length. These length changes are generally measured manually. This task is not only laborious but has the potential for inadvertent bias and error. Here, we present a fully automated and robust approach to detect and track MT dynamics that is not only faster than the present manual approach, but it also provides significantly more and higher quality data, which in turn enables novel analyses to be performed. The proposed tracking algorithm addresses issues such as fast growth and shortening of the MTs-often more than 10 pixels from frame to frame, and frequent occlusion and high clutter, using a spatiotemporal contour tracking approach. Experimental results show that highly accurate tracking results can be obtained in a fully automated manner. The output of our tracking method is currently being used in building descriptive mathematical models for capturing the MT dynamics.
VRL, ECE, UCSB, Jun. 2005.
Node ID: 439 ,
DB ID: 242 ,
Lab: VRL ,
Target: Technical Report