Abstract
This paper presents a novel method of optimizing point-based correspondence among populations of human cortical surfaces by combining structural cues with probabilistic connectivity maps. The proposed method establishes a tradeoff between an even sampling of the cortical surfaces (a low surface entropy) and the similarity of corresponding points across the population (a low ensemble entropy). The similarity metric, however, isn’t constrained to be just spatial proximity, but uses local sulcal depth measurements as well as probabilistic connectivity maps, computed from DWI scans via a stochastic tractography algorithm, to enhance the correspondence definition. We propose a novel method for projecting this fiber connectivity information on the cortical surface, using a surface evolution technique. Our cortical correspondence method does not require a spherical parameterization. Experimental results are presented, showing improved correspondence quality demonstrated by a cortical thickness analysis, as compared to correspondence methods using spatial metrics as the sole correspondence criterion.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Fischl, B., Sereno, M.I., Dale, A.M.: Cortical surface-based analysis II: Inflation, flattening, and a surface-based coordinate system. NeuroImage 9, 195–207 (1999)
Fischl, B., Sereno, M., Tootell, R., Dale, A.: High-res. intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 272–284 (1999)
Tosun, D., Prince, J.: Cortical surface alignment using geometry driven multispectral optical flow. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 480–492. Springer, Heidelberg (2005)
Styner, M., Xu, S., El-Sayed, M., Gerig, G.: Correspondence evaluation in local shape analysis and structural subdivision. In: ISBI, pp. 1192–1195 (2007)
Oguz, I., Cates, J., Fletcher, T., Whitaker, R., Cool, D., Aylward, S., Styner, M.: Cortical correspondence using entropy-based particle systems and local features. In: IEEE Symposium on Biomedical Imaging, ISBI 2008, pp. 1637–1640 (2008)
Styner, M., Rajamani, K., Nolte, L., Zsemlye, G., Székely, G., Taylor, C., Davies, R.: Evaluation of 3D correspondence methods for model building. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 63–75. Springer, Heidelberg (2003)
Kotcheff, A.C., Taylor, C.J.: Automatic construction of eigenshape models by direct optimization. Medical Image Analysis 2(4), 303–314 (1998)
Davies, R., Twining, C., Cootes, T., Waterton, J., Taylor, C.: A minimum description length approach to statistical shape modeling. TMI 21(5), 525–537 (2002)
Brechbühler, C., Gerig, G., Kübler, O.: Parametrization of closed surfaces for 3-D shape description. CVIU 61, 154–170 (1995)
Styner, M., Oguz, I., Heimann, T., Gerig, G.: Minimum description length with local geometry. In: Proc. ISBI, pp. 283–1286 (2008)
Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley-Intersc., Chichester (1991)
Cates, J., Fletcher, T., Whitaker, R.: Entropy-based particle systems for shape correspondence. In: MFCA Workshop, MICCAI 2006, pp. 90–99 (2006)
Cates, J., Fletcher, T., Styner, M., Shenton, M., Whitaker, R.: Shape modeling and analysis with entropy-based particle systems. In: Karssemeijer, N., Lelieveldt, B. (eds.) IPMI 2007. LNCS, vol. 4584, pp. 333–345. Springer, Heidelberg (2007)
Basser, P.J., Pajevic, S., Pierpaoli, C., Duda, J., Aldroubi, A.: In vivo fiber tractography using DT-MRI data. Magnetic Resonance in Medicine 44, 625–632 (2000)
Friman, O., Westin, C.F.: Uncertainty in white matter fiber tractography. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, pp. 107–114. Springer, Heidelberg (2005)
Behrens, T., Woolrich, M., Jenkinson, M., Johansen-Berg, H., Nunes, R., Clare, S., Matthews, P., Brady, J., Smith, S.: Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Mag. Res. Med. 50, 1077–1088 (2003)
Jones, D., Pierpaoli, C.: Confidence mapping in DT-MRI tractography using a bootstrap approach. Mag. Res. Med. 53, 1143–1149 (2005)
Prastawa, M., Gilmore, J., Lin, W., Gerig, G.: Automatic segmentation of MR images of the developing newborn brain. In: Medical Image Analysis, pp. 457–466 (2005)
Tosun, D., Rettmann, M., Prince, J.: Mapping techniques for aligning sulci across multiple brains. Medical Image Analysis 8(3), 295–309 (2004)
Meyer, M., Desbrun, M., Schroder, P., Barr, A.: Discrete differential-geometry operators for triangulated 2-manifolds. VisMath, 35–57 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Oguz, I. et al. (2009). Cortical Correspondence with Probabilistic Fiber Connectivity. In: Prince, J.L., Pham, D.L., Myers, K.J. (eds) Information Processing in Medical Imaging. IPMI 2009. Lecture Notes in Computer Science, vol 5636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02498-6_54
Download citation
DOI: https://doi.org/10.1007/978-3-642-02498-6_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02497-9
Online ISBN: 978-3-642-02498-6
eBook Packages: Computer ScienceComputer Science (R0)