Distortion-optimal self-calibrating parallel MRI by blind interpolation in subsampled filter banks

Behzad Sharif, Yoram Bresler

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

Abstract

Self-calibrating k-space-based image reconstruction in parallel MRI interpolates the subsampled multi-channel data to a fully sampled Nyquist grid in k-space. Adopting a filter bank interpolation framework, we provide a new formulation of the associated inverse problem and develop the theory for blind identification of the interpolant filters. The developed method is applied to imaging scenarios where high effective acceleration is desired and is shown to be capable of reconstructing artifact-free images with minimal amount of calibration data hence, achieving high effective accelerations. Simulation and in-vivo results indicate that improved image quality, and thus greater scan time reductions compared to the state-of-the-art method of GRAPPA can be achieved.

Original languageEnglish (US)
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages52-56
Number of pages5
DOIs
StatePublished - 2011
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: Mar 30 2011Apr 2 2011

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period3/30/114/2/11

Keywords

  • Blind Identification
  • Image Reconstruction
  • MIMO
  • Multi-channel Interpolation
  • Parallel MRI
  • Self-calibrating

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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