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A graphical user interface (GUI) has been developed which enables interactive feedback and control to the real-time diminishing variance algorithm (DVA). This interactivity allows the user to set scan parameters, view scan statistics, and view image updates during the course of the scan. In addition, the DVA has been extended to simultaneously reduce motion artifacts in three dimensions using three orthogonal navigators. Preliminary in vivo studies indicate that these improvements to the standard DVA allow for significantly improved consistency and robustness in eliminating respiratory motion artifacts from MR images, particularly when imaging the coronary arteries.

A cardiac motion compensation method using magnetic resonance signal-based triggering is presented. The method interlaces a triggering pulse sequence with an imaging sequence. The triggering sequence is designed to measure aortic blood velocity, from which cardiac phase can be inferred. The triggering sequence is executed repeatedly and the acquired data processed after each sequence iteration. When the desired phase of the cardiac cycle is detected, data are acquired using the imaging sequence. A signal-processing unit of a conventional scanner is used to process the triggering data in real time and issue triggering commands. Alternatively, a workstation, with a bus adaptor, can access data as they are acquired, process and display the data, and issue triggering commands. With a graphical user interface, the triggering pulse sequence and data-processing techniques can be modified instantaneously to optimize triggering. The technique is demonstrated with coronary artery imaging using both conventional two-dimensional Fourier transform scans and spiral trajectories.

In this work, three-dimensional (3D) spiral imaging has been utilized for magnetic resonance coronary angiography. Spiral-based 3D techniques can dramatically reduce imaging time requirements compared with 3D Fourier Transform imaging. The method developed here utilized a "stack of spirals" trajectory, to traverse 3D k-space rapidly. Both thick-slab volumes encompassing the entire coronary tree with isotropic resolution and thin-slab volumes targeted to a particular vessel of interest were acquired. Respiratory compensation was achieved using the diminishing variance algorithm. T2-prepared contrast was also applied in some cases to improve contrast between vessel and myocardium, while off-resonance blurring was minimized by applying a linear correction to the acquired data. Images from healthy volunteers were displayed using a curved reformatting technique to view long segments of vessel in a single projection. The results demonstrate that this 3D spiral technique is capable of producing high-quality coronary magnetic resonance angiograms.

A technique has been developed whereby motion can be detected in real time during the acquisition of data. This enables the implementation of several algorithms to reduce or eliminate motion effects from an image as it is being acquired. One such algorithm previously described is the acceptance/rejection method. This paper deals with another real-time algorithm called the diminishing variance algorithm (DVA). With this method, a complete set of preliminary data is acquired along with information about the relative motion position of each frame of data. After all the preliminary data are acquired, the position information is used to determine which data frames are most corrupted by motion. Frames of data are then reacquired, starting with the most corrupted one. The position information is continually updated in an iterative process; therefore, each subsequent reacquisition is always done on the worst frame of data. The algorithm has been implemented on several different types of sequences. Preliminary in vivo studies indicate that motion artifacts are dramatically reduced.

A technique has been developed whereby motion can be detected in real time during the acquisition of data. This enables the implementation of an algorithm to accept or reject and reacquire data during a scan. Frames of data with motion are rejected and reacquired on the fly so that by the end of the scan, a complete motion-free data set has been acquired. The algorithm has been implemented on several different types of sequences. Preliminary in vivo studies indicate that motion artifacts are dramatically reduced.