Abstract
Automatic parcellation of cortical surfaces into sulci or gyri based regions is of great importance in studying the structure and function of the human brain. This paper presents a novel method for automatic parcellation of cortical surfaces into gyri based regions. The method is composed of two major steps: data-driven gyral patch segmentation and model-driven gyral patch labeling. The gyral patch segmentation is achieved by several steps, including sulcal region segmentation, sulcal basin parcellation, gyral crest segments extraction and gyral patch segmentation. The gyral patch labeling is formulated as an energy minimization problem, in which a cortical probabilistic atlas and the curvature information on surfaces are used to define the energy function. The energy function is efficiently solved by the graph cuts method. A unique feature of the proposed method is that it does not require high dimensional spatial normalization on images or surfaces. The method has been successfully applied to cortical surfaces of 15 young healthy brain MR images. Quantitative and qualitative evaluation results demonstrate the validity of the proposed method.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Cachia, A., Mangin, J.F., Rivière, D., Papadopoulos-Orfanos, D., Kherif, F., Bloch, I., Régis, J.: A generic framework for the parcellation of the cortical surface into gyri using geodesic Voronoï diagrams. Med. Image Anal. 7(4), 403–416 (2003)
Liu, T., Shen, D., Davatzikos, C.: Deformable registration of cortical structures via hybrid volumetric and surface warping. NeuroImage 22(4), 1790–1801 (2004)
Fischl, B., van der Kouwe, A., Destrieux, C., Halgren, E., Ségonne, F., Salat, D.H., Busa, E., Seidman, L.J., Goldstein, J., Kennedy, D., Caviness, V., Makris, N., Rosen, B., Dale, A.M.: Automatically parcellating the human cerebral cortex. Cereb. Cortex 14(1), 11–22 (2004)
Desikan, R.S., Ségonne, F., Fischl, B., Quinn, B.T., Dickerson, B.C., Blacker, D., Buckner, R.L., Dale, A.M., Maguire, R.P., Hyman, B.T., Albert, M.S., Killiany, R.J., et al.: An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31(3), 968–980 (2006)
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Trans. PAMI. 20(12), 1222–1239 (2001)
Li, G., Guo, L., Nie, J., Liu, T.: Automatic cortical sulcal parcellation based on surface principal direction flow field tracking. NeuroImage 46(4), 923–937 (2009)
Li, G., Guo, L., Li, K., Nie, J., Liu, T.: Gyral parcellation of cortical surfaces via coupled flow field tracking. In: SPIE Medical Imaging, vol. 7623 (2010)
Yeo, B.T., Sabuncu, M.R., Desikan, R., Fischl, B., Golland, P.: Effects of registration regularization and atlas sharpness on segmentation accuracy. Med. Image Anal. 12(5), 603–615 (2008)
Shattuck, D.W., Mirza, M., Adisetiyo, V., Hojatkashani, C., Salamon, G., Narr, K.L., Poldrack, R.A., Bilder, R.M., Toga, A.W.: Construction of a 3D probabilistic atlas of human cortical structures. NeuroImage 39(3), 1064–1080 (2008)
Murphy, K.P., Weiss, Y., Jordan, M.I.: Loopy belief propagation for approximate inference: An empirical study. In: Proc. of Uncertainty in AI 1999, pp. 467–475 (1999)
Kolmogorov, V., Zabih, R.: What energy functions can be minimized via graph cuts. IEEE Trans. PAMI 26(2), 147–159 (2004)
Liu, T., Nie, J., Tarokh, A., Guo, L., Wong, S.T.: Reconstruction of central cortical surface from brain MRI images: method and application. NeruoImage 40(3), 991–1002 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, G., Guo, L., Zhang, T., Nie, J., Liu, T. (2010). Automatic Cortical Gyral Parcellation Using Probabilistic Atlas and Graph Cuts . In: Liao, H., Edwards, P.J."., Pan, X., Fan, Y., Yang, GZ. (eds) Medical Imaging and Augmented Reality. MIAR 2010. Lecture Notes in Computer Science, vol 6326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15699-1_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-15699-1_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15698-4
Online ISBN: 978-3-642-15699-1
eBook Packages: Computer ScienceComputer Science (R0)