Medical Image Analysis
Volume 12, Issue 5 , Pages 616-625 , October 2008

Homeomorphic brain image segmentation with topological and statistical atlases

Received 31 January 2008 ,Revised 14 May 2008 ,Accepted 10 June 2008.

References 

  1. Akselrod-Ballin, A., Galun, M., Gomori, J., Brandt, A., Basri, R., 2007. Prior knowledge driven multiscale segmentation of brain MRI. In: Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’07), Brisbane.
  2. Bazin P-L, Cuzzocreo J, Yassa MA, Gandler W, McAuliffe M, Bassett S, et al. Volumetric neuroimage analysis extensions for the MIPAV software package. Journal of Neuroscience Methods. 2007;165:111–121
  3. Bazin, P.-L., Ellingsen, L., Pham, D., 2007b. Digital homeomorphisms in deformable registration. In: Proceedings of the International Conference on Information Processing in Medical Imaging 2007 (IPMI’07), Kerkrade.
  4. Bazin, P.-L., Pham, D., 2007a. Statistical and topological atlas based brain image segmentation. In: Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’07), Brisbane.
  5. Bazin P-L, Pham D. Topology correction of segmented medical images using a fast marching algorithm. Computer Methods and Programs in Biomedicine. 2007;88(2):182–190
  6. Bazin P-L, Pham D. Topology-preserving tissue classification of magnetic resonance brain images. IEEE Transactions on Medical Imaging. 2007;26(4):special Issue on Computational Neuroanatomy
  7. Bertrand G. Simple points, topological numbers and geodesic neighborhood in cubic grids. Pattern Recognition Letters. 1994;15(10):1003–1011
  8. Christensen GE, Joshi SC, Miller MI. Volumetric transformation of brain anatomy. IEEE Transactions on Medical Imaging. 1997;16(6):864–877
  9. Ciofolo, C., Barillot, C., 2005. Brain segmentation with competitive level sets and fuzzy control. In: Proceedings of the International Conference on Information Processing in Medical Imaging 2005 (IPMI’05), Glenwood Springs.
  10. Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani N, Holmes C, et al. Design and construction of a realistic digital brain phantom. IEEE Transactions on Medical Imaging. 1998;17(3):
  11. Comi A. Pathophysiology of Sturge–Weber syndrome. Journal of Child Neurology. 2003;18(8):509–516
  12. Cootes TF, Edwards GJ, Taylor CJ. Active appearance models. Lecture Notes in Computer Science. 1998;1407:484–498
  13. Corso, J.J., Tu, Z., Yuille, A., Toga, A., 2007. Segmentation of sub-cortical structures by the graph-shifts algorithm. In: Proceedings of the International Conference on Information Processing in Medical Imaging 2007 (IPMI’07), Kerkrade.
  14. Davatzikos C, Tao X, Shen D. Hierarchical active shape models, using the wavelet transform. IEEE Transactions of Medical Imaging. 2003;22(3):414–423
  15. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341–355
  16. Han X, Xu C, Prince JL. A topology-preserving level set method for geometric deformable models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2003;25(6):755–768
  17. Heimann, T., Munzing, S., Meinzer, H.-P., Wolf, I., 2007. A shape-guided deformable model with evolutionary algorithm initialization for 3D soft tissue segmentation. In: Proceedings of the International Conference on Information Processing in Medical Imaging 2007 (IPMI’07), Kerkrade.
  18. Leemput KV, Maes F, Vandermeulen D, Suetens P. Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging. 1999;18(10):897–908
  19. Leventon, M., Faugeraus, O., Grimson, W., 2000. Level set based segmentation with intensity and curvature priors. In: Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis, pp. 4–11.
  20. Li H, Yezzi A, Cohen L. 3D brain segmentation using dual-front active contours with optional user interaction. International Journal of Biomedical Imaging. 2006;1–17
  21. Lu C, Pizer S, Joshi S, Jeong J-Y. Statistical multi-object shape models. International Journal of Computer Vision. 2007;
  22. Malandain G, Bertrand G, Ayache N. Topological segmentation of discrete surfaces. International Journal of Computer Vision. 1993;10(2):183–197
  23. Mangin J-F, Frouin V, Bloch I, Regis J, Lopez-Krahe J. From 3D magnetic resonance images to structural representations of the cortex topography using topology-preserving deformations. Journal of Mathematical Imaging and Vision. 1995;5:297–318
  24. McAuliffe, M., Lalonde, F., McGarry, D., Gandler, W., Csaky, K., Trus, B., 2001. Medical image processing, analysis and visualization in clinical research. In: Proceedings of the 14th IEEE Symposium on Computer-Based Medical Systems (CBMS 2001).
  25. Nempont, O., Atif, J., Angelini, E., Bloch, I., 2007. Combining radiometric and spatial structural information in a new metric for minimal surface segmentation. In: Proceedings of the International Conference on Information Processing in Medical Imaging 2007 (IPMI’07), Kerkrade.
  26. Pham, D., Bazin, P.-L., 2006. Simultaneous registration and tissue classification using clustering algorithms. In: Proceedings of the IEEE International Symposium on Biomedical Imaging, Arlington.
  27. Pham DL. Spatial models for fuzzy clustering. Computer Vision and Image Understanding. 2001;84:285–297
  28. Pohl KM, Fisher J, Bouix S, Shenton ME, McCarley RW, Grimson WEL, et al. Using the logarithm of odds to define a vector space on probabilistic atlases. Medical Image Analysis. 2007;11:465–477
  29. Pohl, K.M., Fisher, J., Levitt, J.J., Shenton, M.E., Kikins, R., Grimson, W.E.L., Wells, W.M., 2005. A unifying approach to registration, segmentation and intensity correction. In: Proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’05), Palm Springs.
  30. Pohl, K.M., Fisher, J., Shenton, M.E., McCarley, R.W., Grimson, W.E.L., Kikins, R., Wells, W.M., 2006. Logarithm odds maps for shape representation. In: Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’06), Copenhagen.
  31. Resnick SM, Pham DL, Kraut MA, Zonderman AB, Davatzikos C. Longitudinal MRI studies of older adults: a shrinking brain. Journal of Neuroscience. 2003;23(8):3295–3301
  32. Rohde GK, Aldroubi A, Dawant BM. The adaptive bases algorithm for intensity-based non-rigid image registration. IEEE Transactions on Medical Imaging. 2003;22(11):1470–1479
  33. Rousson, M., Paragios, N., 2002. Shape priors for level set representations. In: Proceedings of the European Conference on Computer Vision, ECCV, pp. 78–92.
  34. Rousson, M., Xu, C., 2006. A general framework for image segmentation using ordered spatial dependency. In: Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’06), Copenhagen.
  35. Shen D, Davatzikos C. HAMMER: Hierarchical attribute matching mechanism for elastic registration. IEEE Transactions on Medical Imaging. 2002;21(11):
  36. Thompson P, Toga A. A framework for computational anatomy. Computing and Visualization in Science. 2002;5:1–12
  37. Tosun, D., Rettmann, M.E., Prince, J.L., 2003. Mapping techniques for aligning sulci across multiple brains. In: Proceedings of the Sixth Annual International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI), Montral.
  38. Tsai, A., III, W. M. W., Tempany, C., Grimson, W. E. L., Willsky, A. S., 2004. Mutual information in coupled multi-shape model for medical image segmentation. Medical Image Analysis 8.
  39. van Ginneken, B., Heimann, T., Styner, M., 2007. 3D segmentation in the clinic: a grand challenge. In: Proceedings of the 3D Segmentation in the Clinic: A Grand Challenge Workshop of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’07), Brisbane.
  40. Worth, A., 1996. Internet brain segmentation repository, <http://www.cma.mgh.harvard.edu/ibsr/>.
  41. Yeo, B.T., Sabuncu, M.R., Desikan, R., Fischl, B., Golland, P., 2007. Effects of registration regularization and atlas sharpness on segmentation accuracy. In: Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI’07), Brisbane.

PII: S1361-8415(08)00060-1

doi: 10.1016/j.media.2008.06.008

Medical Image Analysis
Volume 12, Issue 5 , Pages 616-625 , October 2008

Article Tools

* Image Usage & Resolution