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Mixture of Segmenters with Discriminative Spatial Regularization and Sparse Weight Selection

  • Ting Chen
  • Baba C. Vemuri
  • Anand Rangarajan
  • Stephan J. Eisenschenk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6893)

Abstract

This paper presents a novel segmentation algorithm which automatically learns the combination of weak segmenters and builds a strong one based on the assumption that the locally weighted combination varies w.r.t. both the weak segmenters and the training images. We learn the weighted combination during the training stage using a discriminative spatial regularization which depends on training set labels. A closed form solution to the cost function is derived for this approach. In the testing stage, a sparse regularization scheme is imposed to avoid overfitting. To the best of our knowledge, such a segmentation technique has never been reported in literature and we empirically show that it significantly improves on the performances of the weak segmenters. After showcasing the performance of the algorithm in the context of atlas-based segmentation, we present comparisons to the existing weak segmenter combination strategies on a hippocampal data set.

Keywords

Training Image Weighted Combination Training Stage Neighborhood Graph Sign Distance Function 
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

  1. 1.
    Carmichael, O.T., Aizenstein, H.A., Davis, S.W., Becker, J.T., Thompson, P.M., Meltzer, C.C., Liu, Y.: Atlas-based Hippocampus Segmentation in Alzheimer’s Disease and Mild Cognitive Impairment. NeuroImage 27(4), 979–990 (2005)CrossRefGoogle Scholar
  2. 2.
    Golland, P., Grimson, W., Shenton, M., Kikinis, R.: Detection and Analysis of Statistical Differences in Anatomical Shape. Med. Image Anal. 9(1), 69–86 (2005)CrossRefGoogle Scholar
  3. 3.
    Morra, J.H., Tu, Z., Apostolova, L.G., Green, A., Toga, A.W., Thompson, P.M.: Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer’s Disease through Automated Hippocampal Segmentation. IEEE Trans. Med. Image 29(1), 30–42 (2010)CrossRefGoogle Scholar
  4. 4.
    Artaechevarria, X., Munoz-Barrutia, A., Ortiz-de-Solorzano, C.: Combination Strategies in Multi-atlas Image Segmentation: Application to Brain MR Data. IEEE Trans. Med. Image 28(8), 1266–1277 (2009)CrossRefGoogle Scholar
  5. 5.
    Khan, A., Cherbuin, N., Wen, W., Anstey, K.J., Sachdev, P., Beg, M.F.: Optimal Weights for Local Multi-atlas Fusion using Supervised Learning and Dynamic Information (SuperDyn): Validation on Hippocampus Segmentation. NeuroImage 56(1), 126–139 (2011)CrossRefGoogle Scholar
  6. 6.
    Kumar, S., Hebert, M.: Discriminative Random Fields. Int. J. Comput. Vision 68(2), 179–201 (2006)CrossRefGoogle Scholar
  7. 7.
    Pohl, K.M., Fisher, J., Shenton, M., McCarley, R.W., Grimson, W.E., Kikinis, R., Wells, W.M.: Logarithm Odds Maps for Shape Representation. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006, Part II. LNCS, vol. 4191, pp. 955–963. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Chen, T., Rangarajan, A., Eisenschenk, S.J., Vemuri, B.C.: Construction of Neuroanatomical Shape Complex Atlas from 3D Brain MRI. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part III. LNCS, vol. 6363, pp. 65–72. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Leventon, M.E., Grimson, W.E.L., Faugeras, O.: Statistical Shape Inuence in Geodesic Active Contours. In: IEEE Conf. CVPR, pp. 316–323 (2000) Google Scholar
  10. 10.
    Zhang, S., Huang, J., Huang, Y., Yu, Y., Li, H., Metaxas, D.: Automatic Image Annotation Using Group Sparsity. In: IEEE Conf. CVPR, pp. 3312–3319 (2010) Google Scholar
  11. 11.
    Frey, B.J., Dueck, D.: Clustering by Passing Messages Between Data Points. Science 315, 972–976 (2007)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ting Chen
    • 1
  • Baba C. Vemuri
    • 1
  • Anand Rangarajan
    • 1
  • Stephan J. Eisenschenk
    • 2
  1. 1.Department of CISEUniversity of FloridaGainesvilleUSA
  2. 2.Department of NeurologyUniversity of FloridaGainesvilleUSA

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