Abstract
We present a method for registration of macroscopic optical images with MR images of the same patient. This forms a key part of a series of procedures to allow post mortem findings to be accurately registered with MR images, and more generally provides a method for 3D mapping of the distribution of pathological changes throughout the brain. The first stage of the method involves a 3D reconstruction of 2D brain slices and was presented in a previous paper [2]. In the current paper, we focus on the registration of the reconstructed volume with corresponding MR images.
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References
P.J. Besl and N.D. McKay. A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2):239–256, 1992.
A.C.F. Colchester, S. Ourselin, Y. Zhu, E. Bardinet, Y. He, A. Roche, S. Al-Sarraj, B. Nailon, J. Ironside, and N. Ayache. 3-D Reconstruction of Macroscopic Optical Brain Slice Images. In S.L. Delp, A.M. DiGioia, and B. Jaramaz, editors, Proceedings of MICCAI’00, volume 1935 of LNCS. Springer, 2000.
F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens. Multimodality Image Registration by Maximization of Mutual Information. IEEE Transactions on Medical Imaging, 16(2):187–198, 1997.
S. Ourselin, A. Roche, G. Subsol, X. Pennec, and N. Ayache. Reconstructing a 3D Structure from Serial Histological Sections. Image and Vision Computing, 19(1-2):25–31, January 2001.
A. Roche, G. Malandain, and N. Ayache. Unifying Maximum Likelihood Approaches in Medical Image Registration. International Journal of Imaging Systems and Technology, 11:71–80, 2000.
A. Roche, X. Pennec, M. Rudolph, D. P. Auer, G. Malandain, S. Ourselin, L. M. Auer, and N. Ayache. Generalized Correlation Ratio for Rigid Registration of 3D Ultrasound with MR Images. In S.L. Delp, A.M. DiGioia, and B. Jaramaz, editors, Proceedings of Medical Imaging Computing And Computer-Assisted Intervention (MICCAI’00), volume 1935 of LNCS, pages 567–577. Springer, 2000.
T. Schormann, M. Von Matthey, A. Dabringhaus, and K. Zilles. Alignment of 3-D Brain Data Sets Originating From MR and Histology. Bioimaging, 1:119–128, 1993.
V. Spitzer, M.J. Ackerman, A.L. Scherzinger, and D. Whitlock. The visible human male: a technical report. Journal of American Medical Informatics Association, 3(2):118–130, 1996.
P. Viola. Alignment byMaximisation of Mutual Information. International Journal of Computer Vision, 24(2):137–154, 1997.
M. Zeidler, R.J. Sellar, D.A. Collie, R. Knight, G. Stewart, M.A. Macleod, J.W. Ironside, S. Cousens, A.C.F. Colchester, D.M. Hadley, and R.G. Will. The pulvinar sign on magnetic resonance imaging in variant Creutzfeldt-Jakob disease. Lancet, 355(9213):1412–1418, April 2000.
Z. Zhang. Iterative Point Matching for Registration of Free-Form Curves and Surfaces. International Journal of Computer Vision, 13(2):119–152, 1994.
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Bardinet, E. et al. (2001). Registration of Reconstructed Post Mortem Optical Data with MR Scans of the Same Patient. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3_114
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DOI: https://doi.org/10.1007/3-540-45468-3_114
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