@phdthesis{garrison2022thesis,
title = {
From Molecules to the Masses: Visual Exploration, Analysis, and Communication
of Human Physiology
},
author = {Laura Ann Garrison},
year = 2022,
month = {September},
isbn = 9788230841389,
url = {https://hdl.handle.net/11250/3015990},
school = {Department of Informatics, University of Bergen, Norway},
abstract = {
The overarching theme of this thesis is the cross-disciplinary application of
medical illustration and visualization techniques to address challenges in
exploring, analyzing, and communicating aspects of physiology to audiences
with differing expertise.
Describing the myriad biological processes occurring in living beings over
time, the science of physiology is complex and critical to our understanding
of how life works. It spans many spatio-temporal scales to combine and bridge
the basic sciences (biology, physics, and chemistry) to medicine. Recent
years have seen an explosion of new and finer-grained experimental and
acquisition methods to characterize these data. The volume and complexity of
these data necessitate effective visualizations to complement standard
analysis practice. Visualization approaches must carefully consider and be
adaptable to the user's main task, be it exploratory, analytical, or
communication-oriented. This thesis contributes to the areas of theory,
empirical findings, methods, applications, and research replicability in
visualizing physiology. Our contributions open with a state-of-the-art report
exploring the challenges and opportunities in visualization for physiology.
This report is motivated by the need for visualization researchers, as well
as researchers in various application domains, to have a centralized,
multiscale overview of visualization tasks and techniques. Using a
mixed-methods search approach, this is the first report of its kind to
broadly survey the space of visualization for physiology. Our approach to
organizing the literature in this report enables the lookup of topics of
interest according to spatio-temporal scale. It further subdivides works
according to any combination of three high-level visualization tasks:
exploration, analysis, and communication. This provides an easily-navigable
foundation for discussion and future research opportunities for audience- and
task-appropriate visualization for physiology. From this report, we identify
two key areas for continued research that begin narrowly and subsequently
broaden in scope: (1) exploratory analysis of multifaceted physiology data
for expert users, and (2) communication for experts and non-experts alike.
Our investigation of multifaceted physiology data takes place over two
studies. Each targets processes occurring at different spatio-temporal scales
and includes a case study with experts to assess the applicability of our
proposed method. At the molecular scale, we examine data from magnetic
resonance spectroscopy (MRS), an advanced biochemical technique used to
identify small molecules (metabolites) in living tissue that are indicative
of metabolic pathway activity. Although highly sensitive and specific, the
output of this modality is abstract and difficult to interpret. Our design
study investigating the tasks and requirements for expert exploratory
analysis of these data led to SpectraMosaic, a novel application enabling
domain researchers to analyze any permutation of metabolites in ratio form
for an entire cohort, or by sample region, individual, acquisition date, or
brain activity status at the time of acquisition. A second approach considers
the exploratory analysis of multidimensional physiological data at the
opposite end of the spatio-temporal scale: population. An effective
exploratory data analysis workflow critically must identify interesting
patterns and relationships, which becomes increasingly difficult as data
dimensionality increases. Although this can be partially addressed with
existing dimensionality reduction techniques, the nature of these techniques
means that subtle patterns may be lost in the process. In this approach, we
describe DimLift, an iterative dimensionality reduction technique enabling
user identification of interesting patterns and relationships that may lie
subtly within a dataset through dimensional bundles. Key to this method is
the user's ability to steer the dimensionality reduction technique to follow
their own lines of inquiry.
Our third question considers the crafting of visualizations for communication
to audiences with different levels of expertise. It is natural to expect that
experts in a topic may have different preferences and criteria to evaluate a
visual communication relative to a non-expert audience. This impacts the
success of an image in communicating a given scenario. Drawing from diverse
techniques in biomedical illustration and visualization, we conducted an
exploratory study of the criteria that audiences use when evaluating a
biomedical process visualization targeted for communication. From this study,
we identify opportunities for further convergence of biomedical illustration
and visualization techniques for more targeted visual communication design.
One opportunity that we discuss in greater depth is the development of
semantically-consistent guidelines for the coloring of molecular scenes. The
intent of such guidelines is to elevate the scientific literacy of non-expert
audiences in the context of molecular visualization, which is particularly
relevant to public health communication.
All application code and empirical findings are open-sourced and available
for reuse by the scientific community and public. The methods and findings
presented in this thesis contribute to a foundation of cross-disciplinary
biomedical illustration and visualization research, opening several
opportunities for continued work in visualization for physiology.
},
pdf = {pdfs/garrison-phdthesis.pdf},
images = {images/garrison-thesis.png},
thumbnails = {images/garrison-thesis-thumb.png},
project = {VIDI}
}
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