Motion artifact reduction and vessel enhancement for free-breathing navigator-gated coronary MRA using 3D k-space reordering.

Breathing-induced bulk motion of the myocardium during data acquisition may cause severe image artifacts in coronary magnetic resonance angiography (MRA). Current motion compensation strategies include breath-holding or free-breathing MR navigator gating and tracking techniques. Navigator-based techniques have been further refined by the applications of sophisticated 2D k-space reordering techniques. A further improvement in image quality and a reduction of relative scanning duration may be expected from a 3D k-space reordering scheme. Therefore, a 3D k-space reordered acquisition scheme including a 3D navigator gated and corrected segmented k-space gradient echo imaging sequence for coronary MRA was implemented. This new zonal motion-adapted acquisition and reordering technique (ZMART) was developed on the basis of a numerical simulation of the Bloch equations. The technique was implemented on a commercial 1.5T MR system, and first phantom and in vivo experiments were performed. Consistent with the results of the theoretical findings, the results obtained in the phantom studies demonstrate a significant reduction of motion artifacts when compared to conventional (non-k-space reordered) gating techniques. Preliminary in vivo findings also compare favorably with the phantom experiments and theoretical considerations. Magn Reson Med 45:645-652, 2001.

Minimum error contrast enhancement

Contrast enhancement is an image processing technique where the objective is to preprocess the image so that relevant information can be either seen or further processed more reliably. These techniques are typically applied when the image itself or the device used for image reproduction provides poor visibility and distinguishability of different regions of interest inthe image. In most studies, the emphasis is on the visualization of image data,but this human observer biased goal often results to images which are not optimal for automated processing. The main contribution of this study is to express the contrast enhancement as a mapping from N-channel image data to 1-channel gray-level image, and to devise a projection method which results to an image with minimal error to the correct contrast image. The projection, the minimum-error contrast image, possess the optimal contrast between the regions of interest in the image. The method is based on estimation of the probability density distributions of the region values, and it employs Bayesian inference to establish the minimum error projection.

Sur le décret du 15 juillet 1791, relatif à l'évasion du roi : adressé à un ami de la constitution, au mois d'août 1791 ([Reprod.]) / par M. Boissy d'Anglas,...

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