Optimization of noisy nonuniform sampling and image reconstruction for fast MRI using a human vision model

K. A. Salem, H. Moriguchi, J. L. Duerk, D. L. Wilson

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


We are developing clinical magnetic resonance imaging (MRI) strategies using spiral acquisition techniques that sample k-space nonuniformly. These methods require a regridding process. Multiple regridding and reconstruction algorithms have been proposed, and we use a perceptual difference model (PDM) to optimize them. We acquired sixteen in vivo MR brain images and simulated reconstruction from a spiral k-space trajectory. Regridding was done by the conventional method of Jackson et al., the block uniform resampling algorithm (BURS), and a newly developed method named matrix rescaling. Each of 16 reference images was reconstructed with multiple parameter sets resulting in a total of over 800 different images. The spiral MR images were compared to the original, fully sampled image using a PDM. Of the three reconstruction methods, the conventional and high-level matrix rescaling methods produce high quality images, but the latter method executed much faster. BURS worked only in extremely low-noise instances, making it often inappropriate. We also demonstrated the effect of display parameters, such as grayscale windowing on image quality. We believe that the PDM techniques provide a promising tool for the evaluation of MR image quality that can aid the engineering design process.

Original languageEnglish (US)
Pages (from-to)82-90
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2001
Externally publishedYes
EventMedical Imaging 2001: Image Perception and Performance - San Diego, CA, United States
Duration: Feb 21 2001Feb 22 2001


  • Image perception
  • Image quality
  • Magnetic resonance imaging
  • Modeling
  • Spiral imaging

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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