RETROSPECTIVE CORRECTION OF SURFACE COIL MR-IMAGES USING AN AUTOMATICSEGMENTATION AND MODELING APPROACH

The use of surface coils in magnetic resonance imaging offers signific ant improvements in the signal-to-noise ratio over volume coils for ma ny applications, However, the inhomogeneous reception profile of surfa ce coils hampers their usefulness by introducing significant nonunifor mities or intensity variations which can vary by greater than six-fold across the sample, In this study, we evaluated an automatic technique for retrospective correction of intensity variations observed in a hi gh-resolution surface coil MR image of the rat brain obtained using an adiabatic magnetic resonance imaging sequence, The images are shown t o have a coefficient of variation less than 12% following application of this correction algorithm, This image intensity correction techniqu e can be applied retrospectively to all data sets and corrects both sa mple/patient dependent effects (e.g. attenuation of overlying tissue) or sample independent effects (e.g. coil geometry or position), This a pproach should also prove valuable in improving regions of interest an alysis, volume histograms and thresholding techniques, (C) 1997 John W iley & Sons, Ltd.