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Visual Exploration of Human Physiology: Visualizing Perfusion, Blood Flow and Aging

Paolo Angelelli

PHDTHESIS, Apr, 2012

Abstract

With the technological advancements in medical imaging, it is nowadays possible to capture in-vivo information related to different human physiological systems. Such data extends the more traditional anatomical scans, but add size, complexity and heterogeneity. In addition, while anatomy data is defined in three-dimensional space, and 3D graphics techniques can be used to represent it on the screen, physiology information is often more abstract, and require tailored solutions to be represented in combination with their anatomical context. This thesis presents solutions for visualizing selected aspects in three domains of physiology: blood flow, perfusion and aging. With respect to blood flow, it includes a technique to enhance the side-by-side visualization of the tubular flow in vessels. This result is achieved with a method that generates straightened visualizations of the flow in its context, which can be easily aligned and then related to each other. With respect to perfusion, this thesis includes an interactive visual analysis solution that ease and improve the exploration, segmentation and analysis of perfusion data acquired using contrast-enhanced ultrasound. This result is achieved by using a statistical framework to extract enhancement information, and an interactive, correlation-based approach to classify the tissue based on similarity. Finally, with respect to aging, two solutions to help exploring large data collections of repeated examinations are presented. In one, interactive visual analysis methods are employed to explore and analyze cohort study data, while the other focuses on the guided exploration of repeated ultrasound examinations. Demonstration case studies are include to exemplify the utility of the presented work.

Published

  • ISBN: 978-82-308-2073-5
  • School: Department of Informatics, University of Bergen, Norway
  • Date: Apr 2012

Media

  • paper
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BibTeX

@phdthesis{angelelli12thesis,
  title = {Visual Exploration of Human Physiology:
            Visualizing Perfusion, Blood Flow and Aging},
  author = {Paolo Angelelli},
  year = {2012},
  abstract = {With the technological advancements in medical imaging, it is nowadays
possible to capture in-vivo information related to different human physiological
systems. Such data extends the more traditional anatomical scans,
but add size, complexity and heterogeneity. In addition, while anatomy
data is defined in three-dimensional space, and 3D graphics techniques can
be used to represent it on the screen, physiology information is often more
abstract, and require tailored solutions to be represented in combination
with their anatomical context.
This thesis presents solutions for visualizing selected aspects in three
domains of physiology: blood flow, perfusion and aging. With respect to
blood flow, it includes a technique to enhance the side-by-side visualization
of the tubular flow in vessels. This result is achieved with a method
that generates straightened visualizations of the flow in its context, which
can be easily aligned and then related to each other. With respect to perfusion,
this thesis includes an interactive visual analysis solution that ease
and improve the exploration, segmentation and analysis of perfusion data
acquired using contrast-enhanced ultrasound. This result is achieved by
using a statistical framework to extract enhancement information, and an
interactive, correlation-based approach to classify the tissue based on similarity.
Finally, with respect to aging, two solutions to help exploring large
data collections of repeated examinations are presented. In one, interactive
visual analysis methods are employed to explore and analyze cohort study
data, while the other focuses on the guided exploration of repeated ultrasound
examinations. Demonstration case studies are include to exemplify
the utility of the presented work.},
  school = {Department of Informatics, University of Bergen, Norway},
  month = {Apr},
  ISBN = {978-82-308-2073-5},



}






 Last Modified: Jean-Paul Balabanian, 2014-11-25