Paper
26 June 2001 Optimization of noisy nonuniform sampling and image reconstruction for fast MRI using a human vision model
Kyle A. Salem, Hisamoto Moriguchi, Jeffrey L. Duerk, David L. Wilson
Author Affiliations +
Abstract
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kyle A. Salem, Hisamoto Moriguchi, Jeffrey L. Duerk, and David L. Wilson "Optimization of noisy nonuniform sampling and image reconstruction for fast MRI using a human vision model", Proc. SPIE 4324, Medical Imaging 2001: Image Perception and Performance, (26 June 2001); https://doi.org/10.1117/12.431176
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Cited by 2 scholarly publications.
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KEYWORDS
Image quality

Signal to noise ratio

Reconstruction algorithms

Magnetic resonance imaging

Brain

Neuroimaging

Visual process modeling

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