L. Le Briquer and J. C. Gee. Design of a Statistical Model of Brain Shape. In J. Duncan and G. Gindi, editors, Lecture Notes in Computer Science: Information Processing in Medical Imaging, volume 1230, pages 477--482, 1997. Home/Search Document Details and Download
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Constructing Data-Driven Optimal Representations for.. - Marsland, Twining (2003) (Correct)
....common frame of reference. This facilitates the modelling of variations in structures between and within disease groups and normals. However, useful analysis requires a common low dimensional representation of the warps. Work to date has either used the densely sampled deformation vectors directly [8], or employed a smooth, continuous representation of them [15] Our data driven algorithm can be extended to generate a common low dimensional representation by choosing new knotpoints based on the errors in the objective function taken over the entire group of images. This extension to groupwise ....
L. LeBriquer and J. Gee. Design of a statistical model of brain shape. In Proceedings of IPMI'97, Lecture Notes in Computer Science 1230, pages 477--482, 1997.
Measuring Geodesic Distances on the Space of Bounded.. - Twining, Marsland, Taylor (2002) (1 citation) (Correct)
....of images, by whatever method. The set of warps that define the correspondence implicitly encode information about the variability of the structures present in the images. Quantifying such anatomical variability via analysis of such sets of warps is the focus of this paper. Previous work (e.g. [3, 11]) has considered the construction of parameterised models of deformation fields. However, there are two possible problems with such approaches. Firstly, the warps they consider are not exact diffeomorphisms the possibility exists for folding or tearing the images. Such a warp is in some sense ....
L. Le Briquer and J. C. Gee. Design of a statistical model of brain shape. In Proceedings of the XVth International Conference on Information Processing in Medical Imaging (IPMI97), volume 1230 of Lecture Notes in Computer Science, pages 477--482. Springer, 1997.
Average Brain Models: A Convergence Study - Guimond, Meunier, Thirion (1999) (5 citations) (Correct)
.... to diagnose abnormal anatomical variations are medical atlases [1] Traditional ones, such as by Talairach Tournoux [2] or Schaltenbrand Wahren [3] are presented in textbooks, but computerized atlases comprising information in a more practical and quantitative manner are becoming available [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]. They usually include information obtained from a set of subjects, as opposed to a single individual in most paper atlases, making them more representative of a population. For example, the Montreal Neurological Institute (MNI) used three hundred and ve (305) normal subjects to build an atlas ....
....measurements conrming their formulation, though we do not compute small deformations as is required for their proof. It should be noted that our resulting model also includes average intensity information and that our respective groups use dioeerent registration methods. Le Briquer and Gee [12] have also developed a method that provides, for a given group of subjects, the mean shape and the modes of principal variation along with their amplitude. Their approach is set in a statistical framework and aims at deriving a shape model. Our method dioeers in that we aim the analysis of local ....
L. Le Briquer and J. C. Gee. Design of a statistical model of brain shape. In J. S. Duncan and G. R. Gindi, editors, Proceedings of the Information Processing in Medical Imaging Conference (IPMI'97), Vermont, United-States, 1997. Springer-Verlag.
Substructural Segmentation Based on Regional Shape Differences - Alexei Machado James (2002) Self-citation (Gee) (Correct)
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L. Le Briquer and J. C. Gee. Design of a Statistical Model of Brain Shape. In J. Duncan and G. Gindi, editors, Lecture Notes in Computer Science: Information Processing in Medical Imaging, volume 1230, pages 477--482, 1997.
Atlas Warping for Brain Morphometry - Alexei Machado And (1998) (3 citations) Self-citation (Gee) (Correct)
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L. Le Briquer and J. Gee, "Design of a statistical model of brain shape," in XV International Conference on Information Processing in Medical Imaging, June 1997.
An Empirical Model Of Brain Shape - Gee, Le Briquer (1997) (3 citations) Self-citation (Le briquer Gee) (Correct)
....processed, each with time proportional to the complexity (size of the basis) of the model under refinement. Evaluation of the method is ongoing, but preliminary studies focused on cerebral anatomy indicate that our approach is capable of capturing subtle shape variations in a population [6,7]. In future work, we will also explore the relationship of our method to approaches for learning generic image models that have been proposed in the machine vision literature [8 12] Acknowledgements This work was supported by the U.S.P.H.S. under grant RO1 NS 33662. The first author is ....
L. Le Briquer and J. C. Gee, "Design of a statistical model of brain shape," in Information Processing in Medical Imaging, J. S. Duncan and G. Gindi, eds., pp. 477--482, SpringerVerlag, Heidelberg, 1997.
A Non-Euclidean Metric for the Classification of Variations.. - Twining, Marsland (2003) (Correct)
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L. LeBriquer & J. Gee. "Design of a statistical model of brain shape." In Proceedings of IPMI'97, volume 1230 of Lecture Notes in Computer Science, pp. 477--482. Springer, 1997.
Automatic Statistical Identification of.. - Guimond, Egorova, .. (2002) (Correct)
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Le Briquer, L., Gee, J.C.: Design of a statistical model of brain shape. In Duncan, J.S., Gindi, G.R., eds.: Proceedings of the IPMI (IPMI'97), Vermont, USA, Springer-Verlag (1997)
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