Dissertation Proposal - University of Houston
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Dissertation Proposal

In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Ming-Chih Shih

will defend his dissertation

Automated Analysis of Flow Cytometry Data for B-Cell Lymphoma


Flow cytometry, a powerful tool for the diagnosis of hematolymphoid malignancies including B-cell lymphomas, is an innovative technique that measures the fluorescence of suspended cells. Traditionally, the method of evaluating the research and clinical study of flow cytometry data is done by the process of manual gating along with a review by pathologists and their accumulated knowledge. The problem with the manual processing is that it is labor-inte nsive, time-consuming, and subject to human error. Although several computerized methods are available for flow cytometry data processing, most of the current automatic techniques have not been fully developed.

In this dissertation through the discoveries found my research, a computational model is proposed to detect B-lymphocyte neoplasms using flow cytometry data by building healthy and sick profiles. The technique is based on using a cell capture rate that is defined to measure the fitness of a test subject using a particular profile. By examining the cell capture rate of a test case with all profiles, the disease type can be determined. To strengthen the system, a confidence level of diagnosis is defined to assist the physician making a better decision. This technique is validated by comparing the diagnosis result with the hospital. In addition, this method is also tested by analyzing test cases of minimal residual disease, obtained from a group of patients with fewer B-cell lymphoma cells, which is a condition, when exhibited, that greatly increase the difficulty of automated diagnosis. Finally, the validity of the automated system is supported by the strong correlation between the results from the automated system diagnosis and the conventional manual process.

Date: Wednesday, April 20, 2016
Time: 5:30 PM
Place: PGH 550
Advisor: Dr. Stephen Huang

Faculty, students, and the general public are invited.