Date of Award
Spring 2010
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical & Computer Engineering
Program/Concentration
Electrical Engineering
Committee Director
Jiang Li
Committee Member
Yuzhong Shen
Committee Member
Frederic D. McKenzie
Call Number for Print
Special Collections LD4331.E55 V353 2010
Abstract
This thesis presents a three-step method to predict prostate cancer (PCa) regions on biopsy tissue samples based on high confident, low resolution PCa regions marked by a pathologist. First, a prediction model is designed to predict PCa regions using matrix-assisted laser desorption mass spectrometry (MALDI-MS) tissue imaging data from one prostate tissue slice. Second, a texture analysis technique is applied to a high magnification optical image for the same purpose from an adjacent tissue slice. Finally, those two results are fused to obtain the PCa regions that will assist MALDI imaging biomarker analysis. Experiments show that the texture analysis based prediction is sensitive but not specific, and the prediction based on the MALDI-MS data is specific while less sensitive. By combing those two results, a much better prediction for PCa regions on the adjacent slice can be achieved. This thesis focuses on the MALDI-MS based PCa region prediction and fusion of prediction from texture analysis and that from MALDI-MS data process mg.
Rights
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DOI
10.25777/8t22-9344
Recommended Citation
Vadlamudi, Ayyappa C..
"Combining Molecular and Imaging Biomarkers to Enhance MALDI Biomarker Analysis"
(2010). Master of Science (MS), Thesis, Electrical & Computer Engineering, Old Dominion University, DOI: 10.25777/8t22-9344
https://digitalcommons.odu.edu/ece_etds/550
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