Colocalization analysis for multimodal optical microscopy
Rao, Yug
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Permalink
https://hdl.handle.net/2142/130067
Description
Title
Colocalization analysis for multimodal optical microscopy
Author(s)
Rao, Yug
Issue Date
2025-07-25
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 Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Colocalization
Microscopy
Label-free Imaging
Image Analysis
Language
eng
Abstract
Novel microscopy techniques allow for the acquisition of multiple modalities of biological images simultaneously. Label-free optical methods take advantage of the molecular, structural, and chemical makeup of biological samples to collect endogenous contrasts without the need for harmful or destructive dyes. While multimodal label-free optical imaging enables many new kinds of biological experiments, there exists an analysis bottleneck between data collection and biological discovery. By calculating “colocalization” metrics to quantify relationships between complementary spatially and temporally co-registered channels, these rich relationships that exist across modalities can begin to be understood. First, synthetic data was used to motivate this exploration, showing that there does not exist one metric that can capture all the various kinds of multimodal relationships that are common in biological data. Then, the significance and value of colocalization features in a breast cancer dataset was explored and its effectiveness against handcrafted morphological features was benchmarked. It was found that not only are there relationships across features and modalities, but by combining information across channels with that within each channel, spatially varying colocalization patterns can be observed. Synthesizing these findings, a colocalization analysis pipeline was applied to three datasets at the tissue-, cellular-, and subcellular-levels to analyze the complex relationships held across channels. Through a thorough study of colocalization signals, it was seen that that inter-channel colocalization relationships contain just as much information as intra-channel morphological relationships in biological tasks, and analysis methods must be carefully tailored to the biological task of interest.
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