University of Houston
Department of Computer Science

In partial fulfillment of the requirements for the Degree of
Doctor of Philosophy


Musodiq O. Bello
will present his thesis proposal

A Statistical Shape and Texture Model for Segmentation of Gene Expression Data



Abstract

To better understand the development and function of the mammalian brain, researchers have begun to systematically collect a large number of gene expression patterns throughout the mouse brain using high throughput in situ hybridization. Associating specific gene activity with specific functional locations in the brain anatomy results in a greater understanding of the role of the gene’s products. To perform such an association for a large amount of data, reliable automated methods that characterize the distribution of gene expression in relation to a standard anatomical model are required.

We propose the development of methods that result in the segmentation of the gene expression image into distinct anatomical regions in which the expression can be quantified and compared with other images. Our methods utilize statistical models of shape, texture, and anatomical landmarks to deform a previously annotated subdivision mesh-based atlas to fit gene expression images. Our experimental data consists of high resolution images of sagittal sections of the adult mouse brain, revealing gene expression patterns.

The resulting large-scale annotation will help scientists interpret gene expression patterns more rapidly and accurately.

Date: Thursday, September 23, 2004
Time: 12:00 PM
Place: 550-PGH

Faculty, students, and the general public are invited.

Thesis Advisor: Prof. Ioannis A. Kakadiaris
Committee Members:
Prof. Yuriy Fofanov, Prof. Ricardo Vilalta, Prof. Joe Warren, and Prof. George Zouridakis