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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.
Sachs et al. (Fri,) studied this question.