Evaluating methods to identify cells in fluorescence microscopy images
Research Mentor(s)
Pollard, Dan A.
Description
Developing efficient and accurate methods is an important aspect of conducting research. A common technique in cell biology is to visualize and quantify proteins in cells using fluorescence microscopy (Snap 2001). The accurate and efficient quantification of proteins, particularly for large numbers of microscopy images, requires a computer based analysis. There are two broad types of methods: using fluorescent cells and using non-fluorescent cells. I propose to evaluate the performance of these methods in two ways: determining how accurate the segmentation is, and evaluating what impact the accuracy has on estimates of gene expression under conditions where cell morphology is changing. The results will help inform cost-benefit analysis of different segmentation approaches.
Document Type
Event
Start Date
17-5-2017 12:00 PM
End Date
17-5-2017 3:00 PM
Department
Biology
Genre/Form
student projects; posters
Subjects – Topical (LCSH)
Cell physiology; Cytofluorometry; Imaging systems in biology
Type
Image
Rights
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this documentation for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.
Language
English
Format
application/pdf
Evaluating methods to identify cells in fluorescence microscopy images
Developing efficient and accurate methods is an important aspect of conducting research. A common technique in cell biology is to visualize and quantify proteins in cells using fluorescence microscopy (Snap 2001). The accurate and efficient quantification of proteins, particularly for large numbers of microscopy images, requires a computer based analysis. There are two broad types of methods: using fluorescent cells and using non-fluorescent cells. I propose to evaluate the performance of these methods in two ways: determining how accurate the segmentation is, and evaluating what impact the accuracy has on estimates of gene expression under conditions where cell morphology is changing. The results will help inform cost-benefit analysis of different segmentation approaches.