Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy
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Yendiki-2011-Automated probabilistic reconstru.pdf
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1.14 MB
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Author(s)
Yendiki, Anastasia
Panneck, Patricia
Srinivasan, Priti
Stevens, Allison
Zollei, Lilla
Augustinack, Jean
Wang, Ruopeng
Salat, David
Ehrlich, Stefan
Behrens, Tim
Date Issued
October 2011
Journal
Frontiers in Neuroinformatics
Publisher
Frontiers Research Foundation
Citation
Yendiki, Anastasia. “Automated Probabilistic Reconstruction of White-Matter Pathways in Health and Disease Using an Atlas of the Underlying Anatomy.” Frontiers in Neuroinformatics 5 (2011): n. pag. © 2011 Frontiers Media
Version
Final published version
Abstract
We have developed a method for automated probabilistic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. Our method is called TRACULA (TRActs Constrained by UnderLying Anatomy) and utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. In this paper we illustrate the application of the method on data from a schizophrenia study and investigate whether the inclusion of both patients and healthy subjects in the training set affects our ability to reconstruct the pathways reliably. We show that, since our method does not constrain the exact spatial location or shape of the pathways but only their trajectory relative to the surrounding anatomical structures, a set a of healthy training subjects can be used to reconstruct the pathways accurately in patients as well as in controls.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.3389/fninf.2011.00023
