Abstract
The creation of average anatomical atlases has been a growing area of research in recent years. It is of increased value to construct representations of, not only intensity atlases, but also their segmentation into required tissues or structures. This paper presents novel groupwise combined segmentation and registration approaches, which aim to simultaneously improve both the alignment of intensity images to their average shape, as well as the segmentations of structures in the average space. An iterative EM framework is used to build average 3D MR atlases of populations for which prior atlases do not currently exist: preterm infants at one- and two-years old. These have been used to quantify the growth of tissues occurring between these ages.
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References
Guimond, A., et al.: Average brain models: A convergence study. Computer Vision and Image Understanding 77(9), 192–210 (2000)
Rueckert, D., et al.: Automatic construction of 3-d statistical deformation models of the brain using nonrigid registration. IEEE TMI 22(8), 1014–1025 (2003)
Joshi, S., Davis, B., Jomier, M., Gerig, G.: Unbiased diffeomorphic atlas construction for computational anatomy. NeuroImage 23, S151–S160 (2004)
Bhatia, K.K., et al.: Consistent groupwise non-rigid registration for atlas construction. In: ISBI 2004, pp. 908–911 (2004)
Christensen, G.E., Johnson, H.J., Vannier, M.W.: Synthesizing average 3D anatomical shapes. NeuroImage 32(1), 146–158 (2006)
Lorenzen, P., et al.: Multi-modal image set registration and atlas formation. Medical Image Analysis 10(3), 440–451 (2006)
Xu, S., et al.: Group mean differences of voxel and surface objects via nonlinear averaging. In: ISBI 2004, pp. 758–761 (2006)
Aljabar, P., et al.: Analysis of growth in the developing brain using non-rigid registration. In: ISBI 2004, pp. 201–204 (2006)
Boardman, J.P., et al.: Abnormal deep grey matter development following preterm birth detected using deformation-based morphometry. NeuroImage 32 (2006)
Kikinis, R., et al.: A digital brain atlas for surgical planning, model-driven segmentation, and teaching. NeuroImage 2, 232–241 (1996)
Hammers, A., et al.: Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. HBM 19, 224–247 (2003)
van Leemput, K., et al.: Automated model-based bias field correction of MR images of the brain. IEEE TMI 18(10), 885–896 (1999)
Wells, W.M., et al.: Adaptive segmentation of MRI data. IEEE TMI 15(4), 429–442 (1996)
Murgasova, M., et al.: Segmentation of brain MRI in young children. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 687–694. Springer, Heidelberg (2006)
D’Agostino, E., et al.: Non-rigid atlas-to-image registration by minimization of class-conditional image entropy. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 745–753. Springer, Heidelberg (2004)
Pohl, K., et al.: A Bayesian model for joint segmentation and registration. NeuroImage 31, 228–239 (2006)
Ashburner, J., Friston, K.: Unified segmentation. NeuroImage 26, 839–851 (2005)
Chen, X., et al.: Simultaneous segmentation and registration of medical image. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 663–670. Springer, Heidelberg (2004)
Petrovic, V., et al.: Automatic framework for medical image registration, segmentation and modeling. In: MIUA 2006 (2006)
Twining, C., et al.: A a unified information-theoretic approach to groupwise non-rigid registration and model building. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 1–14. Springer, Heidelberg (2005)
Meng, X.L., Rubin, D.B.: Maximum likelihood estimation via the ECM algorithm: A general framework. Biometrika 80(2), 267–278 (1993)
Rueckert, D., et al.: Non-rigid registration using free-form deformations: Application to breast MR images. IEEE TMI 18(8), 712–721 (1999)
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Bhatia, K.K. et al. (2007). Groupwise Combined Segmentation and Registration for Atlas Construction. 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 4791. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75757-3_65
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DOI: https://doi.org/10.1007/978-3-540-75757-3_65
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