Model-based quantitative combinatorial optical microscopy for extracting clinical imaging biomarkers

In recent years, many noninvasive, high-resolution biomedical optical imaging techniques based on unique, yet complementary, contrast mechanisms have emerged. While each imaging modality is able to elucidate certain properties of the particular sample under study, an integrated approach in which all modalities are acquired in a simultaneous, co-registered manner can prove advantageous in obtaining a more complete understanding of the sample under study. While this multimodal approach to biomedical imaging is beginning to find more widespread use, thus far most applications of these techniques have been purely qualitative, ignoring the incredibly dense, multidimensional datasets acquired. This thesis presents the framework and several applications of a quantitative model-based combinatorial analysis method. The analysis technique developed provides a direct link between multimodal image contrast and physiological biomarkers. Applications include identification of tissue constituents in fixed tissue slices and classification of cell death mechanisms in a living engineered tissue sample.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Bower, Andrew

Contributors dc:contributor

• Boppart, Stephen A.

• Multimodal Microscopy
• Multiphoton Imaging
• Image Analysis

Statement dc:rights

• Copyright 2014 Andrew Bower

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/73084

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/73084