MS defense: Image Classification and Automated...
MS Thesis Defense
Image Classification and Automated Extraction
of Collocated Actin/Myosin Regions
Ronil S. Mokashi
10:00am Friday, 17 June 2011, ITE 325b
This study illuminates the aspects of cell migration, which is central to many biological processes. To understand cell migration we examine the relationship between local cytoskeletal features and local morphology. We demonstrate this relationship on cells stained for Actin and Myosin We connect the actin/myosin collocalizated structural organization to movements such as membrane protrusions. Membrane protrusions are good indicators of cell migration. Cells can sense the mechanical stiffness or the chemical identity of the surfaces they attach to. We show that these surfaces impact cytoskeletal structure. We develop a classifier to correlate the contextual features extracted from actin/myosin collocalized structure to different cell surfaces.
We also describe a new distance based metric to measure the strength of collocated multi-channel two dimensional data for user selected regions. We provide tools, implemented as plugins for the popular ImageJ toolkit, that are available for download by the general public. These tools allow biologists to specify and score regions of interest by drawing a polygon on their image with a point and click interface. Furthermore, we provide an algorithm that automatically identifies, annotates, and scores an interesting donut shaped region commonly occurring in vascular smooth muscle cells on extra cellular matrix such as dry collagen, wet collagen, fibronectin and monolayer collagen.
Committee:
- Dr. Yaacov Yesha (Chair)
- Dr. Yelena Yesha
- Dr. Michael Grasso
Posted: June 15, 2011, 12:09 AM