Paper
6 April 1995 Statistical best bases for fast encoding in magnetic resonance imaging
Author Affiliations +
Abstract
We discuss the advantages and disadvantages of using a Karhunen-Loeve (K-L) expansion of a training set of images to reduce the number of encodes required for a magnetic resonance (MR) image of a new object. One form of this technique has been proposed and another implemented. We evaluate the error likely to be achieved as a function of the number of encodes and two technical problems: reduced SNR in the images and smoothing of the K-L functions in practice. As an alternative, we propose the use of joint best bases derived from the local trigonometric library as an approximation to the K-L basis. These bases approach the rate-distortion characteristic achieved by the K-L basis, but they are easier to use in MRI and can be applied with existing methods for fast acquisition.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dennis M. Healy Jr., Douglas W. Warner, and John B. Weaver "Statistical best bases for fast encoding in magnetic resonance imaging", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205440
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Magnetic resonance imaging

Computer programming

Signal to noise ratio

Magnetism

Fourier transforms

Data acquisition

Wavelets

RELATED CONTENT

Fast updating in MRI via multiscale localization
Proceedings of SPIE (November 01 1993)
Faster MR Imaging Methods
Proceedings of SPIE (May 05 1986)
Volumetric segmentation of magnetic resonance images
Proceedings of SPIE (September 21 1994)

Back to Top