Abstract
We present a novel automatic multiscale algorithm applied to segmentation of anatomical structures in brain MRI. The algorithm which is derived from algebraic multigrid, uses a graph representation of the image and performs a coarsening process that produces a full hierarchy of segments. Our main contribution is the incorporation of prior knowledge information into the multiscale framework through a Bayesian formulation. The probabilistic information is based on an atlas prior and on a likelihood function estimated from a manually labeled training set. The significance of our new approach is that the constructed pyramid, reflects the prior knowledge formulated. This leads to an accurate and efficient methodology for detection of various anatomical structures simultaneously. Quantitative validation results on gold standard MRI show the benefit of our approach.
Chapter PDF
Similar content being viewed by others
Keywords
- Brain Magnetic Resonance Image
- Aggregative Feature
- Bayesian Formulation
- Probabilistic Atlas
- Brain Segmentation
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
Zijdenbos, A., Forghani, R., Evans, A.: Automatic pipeline analysis of 3D MRI data for clinical trials: application to MS. IEEE TMI 21(10), 1280–1291 (2002)
Pham, D., Xu, C., Prince, J.: Current methods in medical image segmentation. Annual Review of Biomedical Engineering 2, 315–337 (2000)
Sonka, M.M., Fitzpatrick, J.M. (eds.): Handbook of Medical Imaging. SPIE (2000)
Van-Leemput, K.: Probabilistic brain atlas encoding using bayesian inference. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 704–711. Springer, Heidelberg (2006)
Pitiot, A., Delingette, H., Thompson, P.M., Ayache, N.: Expert knowledge guided segmentation system for brain MRI. NeuroImage 23(1), S85–S96 (2004)
Ciofolo, C., Barillot, C.: Brain segmentation with competitive level sets and fuzzy control. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 333–344. Springer, Heidelberg (2005)
Pham, D., Prince, J.: Adaptive fuzzy segmentation of magnetic resonance images. IEEE TMI 18, 737–752 (1999)
Wells, W.M., Grimson, W., Kikinis, R., Jolesz, F.A.: Adaptive segmentation of MRI data. IEEE TMI 15, 429–442 (1996)
Pohl, K., Bouix, S., Kikinis, R., Grimson, W.: Anatomical guided segmentation with non-stationary tissue class distributions in an expectation-maximization framework. IBSI, 564–572 (2004)
Fischl, B., Salat, D., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S.: Whole Brain SegmentationAutomated Labeling of Neuroanatomical Structures in the Human Brain. Neuron 33(3), 341–355 (2002)
Akselrod-Ballin, A., Galun, M., Gomori, J.M., Basri, R., Brandt, A.: Atlas guided identification of brain structures by combining 3D segmentation and SVM classification. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, Springer, Heidelberg (2006)
Galun, M., Sharon, E., Basri, R., Brandt, A.: Texture segmentation by multiscale aggregation of filter responses and shape elements. In: ICCV, pp. 716–723 (2003)
Nain, D., Haker, S., Bobick, A., Tannenbaum, A.: Shape-driven 3D segmentation using spherical wavelets. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, Springer, Heidelberg (2006)
Smith, S.: Fast robust automated brain extraction. Human Brain Mapping 17(3), 143–155 (2002)
Woods, R., Grafton, S., Holmes, C., Cherry, S., Mazziotta, J.: Automated image registration: I. general methods and intrasubject, intramodality validation. Journal of Computer Assisted Tomography 22, 139–152 (1998)
Dawant, B.M., Hartmann, S.L., Thirion, J., Maes, F., Vandermeulen, D., Demaerel, P.: Automatic 3D segmentation of internal structures of the head in MRI using a combination of similarity and free-form transformations. IEEE TMI 18 (1999)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Akselrod-Ballin, A., Galun, M., Gomori, J.M., Brandt, A., Basri, R. (2007). Prior Knowledge Driven Multiscale Segmentation of Brain MRI. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75759-7_15
Download citation
DOI: https://doi.org/10.1007/978-3-540-75759-7_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75758-0
Online ISBN: 978-3-540-75759-7
eBook Packages: Computer ScienceComputer Science (R0)