University of Illinois Urbana-Champaign

Peripheral perfusion imaging modeling

Zhu, Yang

Content Files
ZHU-DISSERTATION-2021.pdf

Permalink

https://hdl.handle.net/2142/113124

Description

Title
Peripheral perfusion imaging modeling
Author(s)
Zhu, Yang
Issue Date
2021-06-21
Director of Research (if dissertation) or Advisor (if thesis)
Insana, Michael F
Doctoral Committee Chair(s)
Insana, Michael F
Committee Member(s)
  • Sutton, Brad
  • Dobrucki, Wawrzyniec
  • Oelze, Michael L
Department of Study
Bioengineering
Discipline
Bioengineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2022-01-12T22:34:45Z
Keyword(s)
  • Ultrasound power Doppler
  • scatterer statistics
  • clutter filtering
  • basis decomposition
  • independent and principal component analyses
Abstract
Effective clutter and noise filtering is critical for contrast-free ultrasonic per- fusion imaging. Novel pulsed-Doppler methods for perfusion imaging are val- idated using dialysis cartridges as perfusion phantoms. Techniques are exam- ined quantitatively at 5 and 12.5 MHz using phantoms with blood-mimicking fluid flow within cellulose microfibers. A variety of flow states are assessed to measurement sensitivity and flow accuracy. Comparisons between phantom and preclinical images show that peripheral perfusion imaging can be reliably achieved without contrast enhancement. One goal is to examine methods for setting the parameters of higher-order singular value decomposition (HOSVD) clutter filter and characterize blood and clutter components. 1-D and 2-D echo simulators are used to model in various flow states and clutter motion with exactly known signals. We explore the strengths and limitations of principal component analysis (PCA) and independent component analysis (ICA) for clutter and noise filtering. PCA methods excel when the echo covariance exhibits a significant blood- scattering component orthogonal to the tissue clutter component. Another goal is to improve the reliability and adaptivity of the HOSVD filter. We evaluate the performance of normalized cross-correlation (NCC) displacement estimation algorithm and Fourier-based registration methods. The remarkable advantage of image registration methods and their ability to help reduce the bandwidth of coherent clutter motion improves the performance of clutter filter on peripheral perfusion imaging.
Graduation Semester
2021-08
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/113124
Copyright and License Information
Copyright 2021 Yang Zhu

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Graduate Theses and Dissertations at Illinois
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