Model-based quantitative combinatorial optical microscopy for extracting clinical imaging biomarkers
Bower, Andrew
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Andrew_Bower.pdf
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https://hdl.handle.net/2142/73084
Description
Title
Model-based quantitative combinatorial optical microscopy for extracting clinical imaging biomarkers
Author(s)
Bower, Andrew
Issue Date
2015-01-21
Director of Research (if dissertation) or Advisor (if thesis)
Boppart, Stephen A.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2015-01-21T19:59:15Z
Keyword(s)
Multimodal Microscopy
Multiphoton Imaging
Image Analysis
Abstract
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.
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Andrew_Bower.pdf
