DocumentCode :
3247630
Title :
Oriented tensor reconstruction: tracing neural pathways from diffusion tensor MRI
Author :
Zhukov, Leonid ; Barr
Author_Institution :
Dept. of Comput. Sci., California Inst. of Technol., Pasadena, CA, USA
fYear :
2002
fDate :
1-1 Nov. 2002
Firstpage :
387
Lastpage :
394
Abstract :
In this paper we develop a new technique for tracing anatomical fibers from 3D tensor fields. The technique extracts salient tensor features using a local regularization technique that allows the algorithm to cross noisy regions and bridge gaps in the data. We applied the method to human brain DT-MRI data and recovered identifiable anatomical structures that correspond to the white matter brain-fiber pathways. The images in this paper are derived from a dataset having 121×88×60 resolution. We were able to recover fibers with less than the voxel size resolution by applying the regularization technique, i.e., using a priori assumptions about fiber smoothness. The regularization procedure is done through a moving least squares filter directly incorporated in the tracing algorithm.
Keywords :
biomedical MRI; data visualisation; eigenvalues and eigenfunctions; interpolation; least squares approximations; 3D tensor fields; a priori assumptions; anatomical fibers tracing; brain-fiber pathways; computer graphics; diffusion tensor MRI; human brain DT-MRI data; identifiable anatomical structures; least squares filter; neural pathways tracing; oriented tensor reconstruction; voxel size resolution; Anatomical structure; Bridges; Data mining; Diffusion tensor imaging; Feature extraction; Humans; Image reconstruction; Magnetic resonance imaging; Neural pathways; Tensile stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visualization, 2002. VIS 2002. IEEE
Conference_Location :
Boston, MA, USA
Print_ISBN :
0-7803-7498-3
Type :
conf
DOI :
10.1109/VISUAL.2002.1183799
Filename :
1183799
Link To Document :
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