Abstract
A procedure for acquisition, automated registration and fusion of functional and anatomical magnetic resonance images (MRI) is presented and validated. The technique is based upon the acquisition of high-resolution anatomical slices at the same spatial locations as functional images (5 slices). The accuracy of registration of these slices and high-resolution 3D MRI volumes (MP-RAGE imaging) was quantified using adapted data originating from the Vanderbilt retrospective registration project (8 patients). Selecting a subset of slices from that data, the small number of images available from fMRI acquisition was taken into account. Quantitative analysis showed no loss of accuracy caused by the reduced number of slices used for registration. For real patient data, fMRI were fused with MP-RAGE images, thus integrating anatomical images with information about locations of functional areas. Via a case study, the benefits of the described approach for intraoperative navigation using an operating microscope (MKM, Zeiss) are demonstrated.
Chapter PDF
Similar content being viewed by others
Keywords
- Blood Oxygenation Level Dependency
- Magnetic Resonance Image Data
- Functional Magnetic Resonance Image
- Registration Accuracy
- Weighted Magnetic Resonance Image
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Frahm, J., Bruhn, H., Merboldt, K.D., Hanicke, W.: Dynamic MR imaging of human brain oxygenation during rest and photic stimulation. J. Magn. Reson. Imaging 2(5), 501–505 (1992)
Thomale, U.-W., Liebig, T., Taschner, C., Rohlfing, T., Beier, J., Rosenthal, A., et al.: Integration of functional MRI data in computer assisted surgery. In: Lemke, H.U., et al. (eds.) Computer Assisted Radiology and Surgery. Elsevier, Amsterdam (1999)
West, J., Fitzpatrick, J.M., Wang, M.Y., Dawant, B.M., Maurer Jr., C.R., Kessler, R.M., et al.: Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques. J. Comput. Assist. Tomogr. 21(4), 554–566 (1997)
Studholme, C., Hill, D.L.G., Hawkes, D.J.: An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognition 32, 71–86 (1998)
Studholme, C., Hill, D.L.G., 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(1), 25–35 (1997)
Hill, D.L., Hawkes, D.J., Crossman, J.E., Gleeson, M.J., Cox, T.C., Bracey, E.E., et al.: Registration of MR and CT images for skull base surgery using point-like anatomical features. Br. J. Radiol. 64(767), 1030–1035 (1991)
Hosten, N., Rohlfing, T., Beier, J., Liebig, T., Lanksch, W., Felix, R.: Registration of CT and MRT images for navigation in image-guided brain surgery. Radiology 209(P), 206 (1998)
Maurer Jr., C.R., Fitzpatrick, J.M., Wang, M.Y., Galloway Jr., R.L., Maciunas, R.J., Allen, G.S.: Registration of head volume images using implantable fiducial markers. IEEE Trans. Med. Imaging 16(4), 447–462 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rohlfing, T., Beier, J., West, J.B., Thomale, U.W., Liebig, T., Taschner, C.A. (1999). Automated Registration and Fusion of Functional and Anatomical MRI for Navigated Neurosurgery. In: Taylor, C., Colchester, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI’99. MICCAI 1999. Lecture Notes in Computer Science, vol 1679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10704282_103
Download citation
DOI: https://doi.org/10.1007/10704282_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66503-8
Online ISBN: 978-3-540-48232-1
eBook Packages: Springer Book Archive