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Determining Gradient Imperfections in NMR Machines

IP.com Disclosure Number: IPCOM000060217D
Original Publication Date: 1986-Mar-01
Included in the Prior Art Database: 2005-Mar-08
Document File: 2 page(s) / 20K

Publishing Venue

IBM

Related People

Feig, E: AUTHOR [+2]

Abstract

In order to correct for the errors in Nuclear Magnetic Resonance (NMR) images due to magnetic inhomogeneities using the self-correcting techniques introduced in the article appearing in the IBM Technical Disclosure Bulletin 28, 4017-4018 (February 1986), one needs a priori determination of the inhomogeneity contributed by the gradients themselves. This article describes a technique to determine these. The following is an outline for the algorithm. We will determine functions A(x,y) and B(x,y) which represent the intensity of the inhomogeneities of the x and y gradients (extensions to three dimensional imaging are obvious), respectively. Step 1: Place an object which is susceptible to NMR excitation and had uniform mass in the bore of the magnet where a field mapping is desired.

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Determining Gradient Imperfections in NMR Machines

In order to correct for the errors in Nuclear Magnetic Resonance (NMR) images due to magnetic inhomogeneities using the self-correcting techniques introduced in the article appearing in the IBM Technical Disclosure Bulletin 28, 4017-4018 (February 1986), one needs a priori determination of the inhomogeneity contributed by the gradients themselves. This article describes a technique to determine these. The following is an outline for the algorithm. We will determine functions A(x,y) and B(x,y) which represent the intensity of the inhomogeneities of the x and y gradients (extensions to three dimensional imaging are obvious), respectively. Step 1: Place an object which is susceptible to NMR excitation and had uniform mass in the bore of the magnet where a field mapping is desired. Step 2: Selectively excite lines y = yOE in the desired plane. Step 3: Use the pulse-gradient sequence shown in the figure, where the initial excitation is the line-excitation of step 2. Step 4: Filter the high oscillatory components and the exponentially decaying envelope from the FID (Function Identification) signal; label the result S(Gxt). Here, Gx parameterizes the x-gradient encoding, and t is a time variable. Step 5: Compute S(x,w), the 2-dimensional Fourier transform of the function S. Step 6: Let T(x) be the maximum of S(x,w) as w ranges over its entire domain. Determine A'(x), where T(x) = 1/(1+A'(x)). Step 7: Determine A(x) from...