A novel filtering approach for 3D harmonic phase analysis of tagged MRI

Xiaokai Wang, Maureen L. Stone, Jerry Ladd Prince, Arnold Gomez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Harmonic phase analysis has been used to perform noninvasive organ motion and strain estimation using tagged magnetic resonance imaging (MRI). The filtering process, which is used to produce harmonic phase images used for tissue tracking, influences the estimation accuracy. In this work, we evaluated different filtering approaches, and propose a novel high-pass filter for volumes tagged in individual directions. Testing was done using an open benchmarking dataset and synthetic images obtained using a mechanical model. We compared estimation results from our filtering approach with results from the traditional filtering approach. Our results indicate that 1) the proposed high-pass filter outperforms the traditional filtering approach reducing error by as much as 50% and 2) the accuracy improvements are especially marked in complex deformations.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationImage Processing
EditorsElsa D. Angelini, Elsa D. Angelini, Bennett A. Landman
PublisherSPIE
Volume10574
ISBN (Electronic)9781510616370
DOIs
StatePublished - Jan 1 2018
EventMedical Imaging 2018: Image Processing - Houston, United States
Duration: Feb 11 2018Feb 13 2018

Other

OtherMedical Imaging 2018: Image Processing
CountryUnited States
CityHouston
Period2/11/182/13/18

Keywords

  • brain
  • Imaging
  • mechanics
  • tongue

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Wang, X., Stone, M. L., Prince, J. L., & Gomez, A. (2018). A novel filtering approach for 3D harmonic phase analysis of tagged MRI. In E. D. Angelini, E. D. Angelini, & B. A. Landman (Eds.), Medical Imaging 2018: Image Processing (Vol. 10574). [1057414] SPIE. https://doi.org/10.1117/12.2293643