The monitoring of the development of cerebral diseases such as stroke or brain tumors with MRI requires high-precision comparison of initial and follow-up images. Retrospective registration often produces artifacts, especially at boundariesbetween different tissue structures. However, by manipulating the gradients, MRI scanners offer the possibility of shifting and rotating image planes fast and without removing the patient. Two approaches for prospective registration were implemented and tested on phantoms and healthy volunteers. To speed up calculation, both registration algorithms used the three orthogonal two-dimensional localizer images that were acquired prior to each measurement. In the first approach, the image is projected onto one axis to determine the rotation between initial and follow-up examination. The second algorithm uses cross-correlation for rotational correction. Both algorithms maximize the cross-correlation for correction of the shifts. After 2-D registration in each orientation, the gradients of the tomograph are adapted according to the calculated transformation matrix. The results were evaluated with a 3-D rigid-body registration using Automated Image Registration. The cross-correlation method was found to be very robust, while the 1-D projection algorithm was sufficiently fast but registration results depended on the shape of the head.
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