Abstract
A generally applicable 3D fusion method was evaluated using molecular imaging and MRI volumetric data sets from 15 brain tumor patients with stereotactic frames attached to their skull. Point pairs, placed on the frame only, were chosen, polynomial warping coefficients were generated to map voxels from one coordinate space to the other. The MRI frame was considered the reference structure and the standard for “correct” registration. An ANOVA test (p > 0.05) confirmed the point pair choice to be consistent. The 95% confidence interval for the t-test showed the measured distance difference between the registered volumes was within one MRI voxel. A further experiment was conducted to independently evaluate the brain registration based on testing for consistency of randomly selected interior/exterior points. A t-test result (p < 0.05) showed that the consistency (i.e., both interior or both exterior) before and after volume registration were significantly different. This fusion method may be a viable alternative when other methods fail.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
REFERENCES
Studholme, C., Hill, D. L. G., and Hawkes, D. J., Automated 3D registration of MR and CT images of the head. Med. Image Anal. 1:163–175, 1996.
West, J. B., and Fitzpatrick, J. M., Point-based rigid registration: Clinical validation of theory. Proc SPIE 3979:353–359, 2000.
Studholme, C., Hill, D. L. G., and Hawkes, D. J., Automated three-dimensional registration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. Med. Phys. 24:25–35, 1997.
Woods, R. P., Mazziotta, J. C., and Cherry, S. R., MRI-PET registration with automated algorithm. J. Comput Assist. Tomogr. 17:536–546, 1993.
Pelizzari, C. A., Chen, G. T. Y., Spelbring, D. R., Weichselbaum, R. R., and Chen, C. T., Accurate three-dimensional registration of CT, PET and/or MR images of the brain. J. Comput. Assist. Tomogr. 13:20–26, 1989.
Van den Elsen, P. A., Pol, E. J. D., and Viergever, M. A., Medical image matching—a review with classification. IEEE Eng. Med. Biol. EMB 40:26–39, 1993.
Maintz, J. B. A., and Viergever, M. A., A survey of medical image registration. Med. Image Anal 2:1–36, 1998.
Schettino, C. J., Noz, M. E., Kramer, E., Taneja, S., and Lepor, H., Impact of image fusion of the 111In Capromab Pendetide with MR or CT in patients with recurrent prostate CA. J. Nucl. Med. 42:294P, 2001.
Gustafsson, A., Lind, B. K., and Brahme, A., A generalized pencil beam algorithm for optimization of radiation therapy. Med. Phys. 21:343–356, 1994.
Källman, P., Lind, B. K., and Brahme, A., An algorithm for maximizing the probability of complication free tumor control in radiation therapy. Phys. Med. Biol. 37:871–890, 1992.
Meyer, C. R., Boes, J. L., Kim, B., Bland, P. H., Zasadny, K. R., Kison, P. V., Koral, K., Frey, K. A., and Wahl, R. L., Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin plate spline warped geometric deformations. Med. Image Anal. 3:195–206, 1996.
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., and Suetens, P., Multimodality image registration by maximization of mutual information. IEEE Transact. Med. Imaging 16:187–198, 1997.
Skouson, M. B., Guo, Q., and Liang, Z. P., A bound on mutual information for image registration. IEEE Transact. Med. Imaging 20:843–846, 1997.
Crafoord, J., Mahmoud, F., Kramer, E. L., Maguire, G. Q., Jr., Noz, M. E., and Zeleznik, M. P., Comparison of two landmark based image registration methods for use with a body atlas. Physica Medica XVI:75–82, 2000.
Noz, M. E., Maguire, G. Q., Jr., Zeleznik, M. P., Kramer, E. L., Mahmoud, F., and Crafoord, J., A versatile functional-anatomic image fusion method for volume data sets. J. Med. Systems 25:297–307, 2001.
Maguire, G. Q., Jr., Noz, M. E., Rusinek, H., Jaeger, J., Kramer, E. L., Sanger, J. J., and Smith, G., Graphics applied to image registration. IEEE Comput Graph. Appl. 11:20–29, 1991.
Pfluger, T., Vollmar, C., Wismüller, A., Dresel, S., Berger, P., Suntheim, P., Leinsinger, G., and Hahn, K., Quantitative comparison of automatic and interactive methods for MRI-SPECT image registration of the brain based on 3-dimensional calculation of error. J. Nucl. Med. 41:1823–1829, 2000.
Rohr, K., Stiehl, H. S., Sprengal, R., Buzug, T. M., Weese, J., and Kuhn, M. H., Landmark-based elastic registration using approximating thin-plate splines. IEEE Transact. Med. Imaging 20:526–534, 2001.
Kramer, E. L., Noz, M. E., Sanger, J. J., Megibow, A., Maguire, G. Q., Jr., CT-SPECT fusion to correlate radiolabeled monoclonal antibody uptake with abdominal CT findings. Radiology 172:861–865, 1989.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gorniak, R.J.T., Kramer, E.L., Maguire, G.Q. et al. Evaluation of a Semiautomatic 3D Fusion Technique Applied to Molecular Imaging and MRI Brain/Frame Volume Data Sets. Journal of Medical Systems 27, 141–156 (2003). https://doi.org/10.1023/A:1021860910856
Issue Date:
DOI: https://doi.org/10.1023/A:1021860910856