Files in this item

FilesDescriptionFormat

application/pdf

application/pdfMustafa_Mir.pdf (5MB)
(no description provided)PDF

Description

Title:Quantitative phase imaging for cellular biology
Author(s):Mir, Mustafa
Director of Research:Popescu, Gabriel
Doctoral Committee Chair(s):Popescu, Gabriel
Doctoral Committee Member(s):Prasanth, Supriya G.; Boppart, Stephen A.; Bashir, Rashid
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Quantitative phase imaging
Spatial light interference microscopy
diffraction phase microscopy
red blood cell cytometry
cell growth
cycle dependent growth
neuronal network organization
cell proliferation
tomography
sub-cellular tomography
image analysis
interferometry
microscopy
Abstract:Measuring cellular level phenomena is challenging because of the transparent nature of cells and tissues, the multiple temporal and spatial scales involved, and the need for both high sensitivity (to single cell density, morphology, motility, etc.) and the ability to measure a large number of cells. Quantitative phase imaging (QPI) is an emerging field that addresses this need. New quantitative phase imaging modalities have emerged that provide highly sensitive information on cellular growth, motility, dynamics and spatial organization. These parameters can be measured from the sub-micron to millimeter scales and timescales ranging from milliseconds to days. In this thesis I discuss the development and use of QPI tools and analysis methods to explore several applications in both clinical and research settings. Through these applications I demonstrate that the quantitative information provided by QPI methods allows for analyzing biological systems in an unprecedented manner, creating opportunities to answer longstanding questions in biological sciences, and also enabling the study of phenomena that were previously inaccessible. Here I show results on blood cell analysis, single cell growth, cellular proliferation assays and neural network formation. These results prove that QPI provides unique and important insight into the behavior of biological systems and can be utilized to help address important needs in clinical settings as well as answer fundamental biological questions.
Issue Date:2013-08-22
URI:http://hdl.handle.net/2142/45668
Rights Information:Copyright 2013 Mustafa Mir
Date Available in IDEALS:2013-08-22
2015-08-22
Date Deposited:2013-08


This item appears in the following Collection(s)

Item Statistics