Abstract
A novel dynamic (4D) PET to PET image registration procedure is proposed and applied to multiple PET scans acquired with the high resolution research tomograph (HRRT), the highest resolution human brain PET scanner available in the world. By extending the recent diffeomorphic log-demons (DLD) method and applying it to multiple dynamic [11C]raclopride scans from the HRRT, an important step towards construction of a PET atlas of unprecedented quality for [11C]raclopride imaging of the human brain has been achieved. Accounting for the temporal dimension in PET data improves registration accuracy when compared to registration of 3D to 3D time-averaged PET images. The DLD approach was chosen for its ease in providing both an intensity and shape template, through iterative sequential pair-wise registrations with fast convergence. The proposed method is applicable to any PET radiotracer, providing 4D atlases with useful applications in high accuracy PET data simulations and automated PET image analysis.
Chapter PDF
Similar content being viewed by others
Keywords
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
Alpert, N., Berdichevsky, D., Levin, Z., Morris, E., Fischman, A.J.: Improved methods for image registration. NeuroImage 3 (1996)
Beg, M., Miller, M., Trouvé, A., Younes, L.: Computing large deformation metric mappings via geodesic flows of diffeomorphisms. IJCV 61 (2005)
Collins, D., Neelin, P., Peters, T., Evans, A.: Automatic 3D intersubject registration of MR volumetric data in standardized talairach space. Journal of Computer Assisted Tomography 18 (1994)
Guimond, A., Meunier, J., Thirion, J.-P.: Automatic computation of average brain models. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 631–640. Springer, Heidelberg (1998)
Gunn, R., Lammertsma, A., Hume, S., Cunningham, V.: Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. Neuroimage 6 (1997)
Hill, D., Batchelor, P., Holden, M., Hawkes, D.: Medical image registration. PMB 46 (2001)
Lammertsma, A., Hume, S.: Simplified reference tissue model for PET receptor studies. Neuroimage 4 (1996)
Lombaert, H., Peyrat, J., Croisille, P., Rapacchi, S., Fanton, L., Cheriet, F., Clarysse, P., Magnin, I., Delingette, H., Ayache, N.: Human atlas of the cardiac fiber architecture: study on a healthy population. TMI 31 (2012)
Peyrat, J.M., Delingette, H., Sermesant, M., Xu, C., Ayache, N.: Registration of 4D cardiac CT sequences under trajectory constraints with multichannel diffeomorphic demons. TMI 29 (2010)
Qin, P., Duncan, N., Wiebking, C., Gravel, P., Lyttelton, O., Hayes, D., et al.: GABAA receptors in visual and auditory cortex and neural activity changes during basic visual stimulation. Frontiers in Human Neuroscience 6 (2012)
Shen, D., Davatzikos, C.: Hammer: hierarchical attribute matching mechanism for elastic registration. TMI 21 (2002)
Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Symmetric log-domain diffeomorphic registration: A demons-based approach. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 754–761. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bieth, M., Lombaert, H., Reader, A.J., Siddiqi, K. (2013). Atlas Construction for Dynamic (4D) PET Using Diffeomorphic Transformations. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. MICCAI 2013. Lecture Notes in Computer Science, vol 8150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40763-5_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-40763-5_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40762-8
Online ISBN: 978-3-642-40763-5
eBook Packages: Computer ScienceComputer Science (R0)