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Biomedical Imaging Resource, Departments of Neurology and Nuclear Medicine, Mayo Foundation, Rochester, Minnesota
Imaging and Visualization, Siemens Corporate Research, Princeton, New Jersey
Correspondence: For correspondence or reprints contact: Richard A. Robb, PhD, Director, Biomedical Imaging Resource, Medical Sciences 2-135, Mayo Foundation, Rochester, MN 55905.
ABSTRACT
This study reports quantitative measurements of the accuracy of two popular voxel-based registration algorithms—Woods' automated image registration algorithm and mutual information correlation—and compares these with conventional surface matching (SM) registration. Methods: The registration algorithms were compared (15 different matches each) for (a) three-dimensional brain phantom images, (b) an ictal SPECT image from a patient with partial epilepsy matched to itself after modification to simulate changes in the cerebral blood flow pattern and (c) ictal/interictal SPECT images from 15 patients with partial epilepsy. Blinded visual ranking and localization of the subtraction images derived from the patient images were also performed. Results: Both voxel-based registration methods were more accurate than SM registration (P < 0.0005). Automated image registration algorithm was more accurate than mutual information correlation for the computer-simulated ictal/interictal images and the patient ictal/interictal studies (P < 0.05). The subtraction SPECTs from SM were poorer in visual ranking more often than the voxel-based methods (P < 0.05). Conclusion: Voxel intensity-based registration algorithms provide significant improvement in ictal/interictal SPECT registration accuracy and result in a clinically detectable improvement in the subtraction SPECT images.
Key Words: image registration • ictal/interictal SPECT • partial epilepsy • cerebral blood flow
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