Tobias Schäffter

Motion compensated projection reconstruction

Over recent years, MRI has shown the capability for real‐time applications. Although the acquisition times of fast MRI methods have been reduced significantly, patient motion during a magnetic resonance imaging (MRI) examination still causes artifacts in the image. In this paper, the effects of motion in MRI using a radial acquisition scheme are examined. It is shown that motion can be estimated without the use of additional measurement, based on the acquired projections only. A new reconstruction technique is introduced that integrates a motion compensation algorithm into the MR‐reconstruction process, resulting in a significant reduction of blurring artifacts in the reconstructed images. The proposed method is applied to different kinds of motion such as kinetic joint studies. Magn Reson Med 41:954–963, 1999.

Correlative averaging for radial magnetic resonance imaging

Abstract Although Magnetic Resonance Imaging (MRI) has faced a dramatic increase in real-time capabilities over the last year, acceptable image quality still limits the actually achievable acquisition speed. This paper presents a motion-compensated noise filter that, on the basis of hierarchical motion estimation and edge-preserving adaptive weighted averaging, has been integrated into a segmented radial MR acquisition scheme. In several studies of moving joints, the proposed approach led to significant reductions in the noise level without introducing motion blur. The improved image quality would, in principle, allow more than double the acquisition speed, retaining the original image quality.

A PROJECTION-BASED METHOD FOR MOTION-COMPENSATED NOISE SUPPRESSION

Abstract The diagnostic value of medical images significantly depends on the signal-to-noise ratio (SNR). Especially in fluoroscopic tomography, the SNR is limited by the radiation dose (Computer Tomography), or by the suitable acquisition techniques (Magnetic Resonance Imaging). The purpose of this paper is to introduce a projection-based method for the motion-compensated SNR enhancement applied in Radon space. It is based on a projection-based motion estimation with subsequent motion-compensated, edge-preserving filtering of the measured projections. The effect of temporal filtering as well as spatial filtering will be presented. In contrast to the recently introduced image-based approach, this method allows a very efficient computational implementation, likely to be used in real time imaging. It will be shown that a significant increase of the SNR can be achieved without introducing additional motion artifacts or blurring in the reconstructed images. The proposed technique has the potential to be used for SNR enhancement in low-dose fluoroscopy applications in CT as well as for SNR improvements in MR fluoroscopy using projection reconstruction based techniques.