Active fibers: Matching deformable tract templates to diffusion tensor images
| Autor: | Ilya Eckstein, Katie L. McMahon, David W. Shattuck, Jason L. Stein, Paul M. Thompson, Greig I. de Zubicaray, Arthur W. Toga, Margaret J. Wright |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Matching (graph theory)
Computer science Cognitive Neuroscience Models Neurological Fornix Brain Article Imaging phantom Tensor field White matter Young Adult Imaging Three-Dimensional Neuroimaging Neural Pathways Image Processing Computer-Assisted medicine Humans Segmentation Computer vision Dti tractography Phantoms Imaging business.industry Fiber (mathematics) Template matching Brain Diffusion Magnetic Resonance Imaging medicine.anatomical_structure Neurology Artificial intelligence business Algorithms Diffusion MRI Tractography |
| Zdroj: | NeuroImage. 47:T82-T89 |
| ISSN: | 1053-8119 |
| DOI: | 10.1016/j.neuroimage.2009.01.065 |
| Popis: | Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the subject tensor field, skipping the fiber tracking step. Furthermore, the use of a common template eliminates the need for tractography segmentation and defines intersubject shape correspondence. The method is validated using phantom DTI data and applications are presented, including automatic fiber-bundle reconstruction and tract-based morphometry. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect