Improved correspondence for DTI population studies via unbiased atlas building

Casey Goodlett; Brad Davis; Remi Jean; John Gilmore; Guido Gerig

doi:10.1007/11866763_32

Improved correspondence for DTI population studies via unbiased atlas building

Casey Goodlett, Brad Davis, Remi Jean, John Gilmore, Guido Gerig

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a method for automatically finding correspondence in Diffusion Tensor Imaging (DTI) from deformable registration to a common atlas. The registration jointly produces an average DTI atlas, which is unbiased with respect to the choice of a template image, along with diffeomorphic correspondence between each image. The registration image match metric uses a feature detector for thin fiber structures of white matter, and interpolation and averaging of diffusion tensors use the Riemannian symmetric space framework. The anatomically significant correspondence provides a basis for comparison of tensor features and fiber tract geometry in clinical studies and for building DTI population atlases.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings
Publisher	Springer Verlag
Pages	260-267
Number of pages	8
ISBN (Print)	354044727X, 9783540447276
DOIs	https://doi.org/10.1007/11866763_32
State	Published - 2006
Event	9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark Duration: Oct 1 2006 → Oct 6 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4191 LNCS - II
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
Country/Territory	Denmark
City	Copenhagen
Period	10/1/06 → 10/6/06

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/11866763_32

Cite this

Goodlett, C., Davis, B., Jean, R., Gilmore, J., & Gerig, G. (2006). Improved correspondence for DTI population studies via unbiased atlas building. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings (pp. 260-267). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4191 LNCS - II). Springer Verlag. https://doi.org/10.1007/11866763_32

Improved correspondence for DTI population studies via unbiased atlas building. / Goodlett, Casey; Davis, Brad; Jean, Remi et al.
Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Springer Verlag, 2006. p. 260-267 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4191 LNCS - II).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Goodlett, C, Davis, B, Jean, R, Gilmore, J & Gerig, G 2006, Improved correspondence for DTI population studies via unbiased atlas building. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4191 LNCS - II, Springer Verlag, pp. 260-267, 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006, Copenhagen, Denmark, 10/1/06. https://doi.org/10.1007/11866763_32

Goodlett C, Davis B, Jean R, Gilmore J, Gerig G. Improved correspondence for DTI population studies via unbiased atlas building. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Springer Verlag. 2006. p. 260-267. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11866763_32

Goodlett, Casey ; Davis, Brad ; Jean, Remi et al. / Improved correspondence for DTI population studies via unbiased atlas building. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings. Springer Verlag, 2006. pp. 260-267 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Improved correspondence for DTI population studies via unbiased atlas building

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