Type of Document Master's Thesis Author Jouenne, Vincent Y URN etd-07112001-112357 Title Critical Issues in the Processing of cDNA Microarray Images Degree Master of Science Department Computer Science Advisory Committee
Advisor Name Title Heath, Lenwood S. Committee Chair Alscher, Ruth G. Committee Member Struble, Craig A. Committee Member Keywords
- Mann-Whitney Test
- Image Processing
- Segmentation
- Gene Expression
- Data Extraction
- Seeded Region Growing Algorithm
- Automatic Gridding
Date of Defense 2001-06-28 Availability unrestricted Abstract Microarray technology enables simultaneous gene expression level
monitoring for thousands of genes. While this technology has now
been recognized as a powerful and cost-effective tool for
large-scale analysis, the many systematic sources of experimental
variations introduce inherent errors in the extracted data. Data
is gathered by processing scanned images of microarray slides.
Therefore robust image processing is particularly important and
has a large impact on downstream analysis. The processing of the
scanned images can be subdivided in three phases: gridding,
segmentation and data extraction. To measure the gene expression
levels, the processing of cDNA microarray images must overcome a
large set of issues in these three phases that motivates this
study.
This study presents automatic gridding methods and compares their
performances. Two segmentation techniques already used, the Seeded
Region Growing Algorithm and the Mann-Whitney Test, are examined.
We present limitations of these techniques. Finally, we studied
the data extraction method used in MicroArray Suite (MS), a
microarray analysis software, via synthetic images and explain its
intricacies.
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