Probabilistic tractography for topographically organized connectomes

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • University of Southern California

Kuvaus

While tractography is widely used in brain imaging research,its quantitative validation is highly difficult. Many fiber systems,however,have well-known topographic organization which can even be quantitatively mapped such as the retinotopy of visual pathway. Motivated by this previously untapped anatomical knowledge,we develop a novel tractography method that preserves both topographic and geometric regularity of fiber systems. For topographic preservation,we propose a novel likelihood function that tests the match between parallel curves and fiber orientation distributions. For geometric regularity,we use Gaussian distributions of Frenet-Serret frames. Taken together,we develop a Bayesian framework for generating highly organized tracks that accurately follow neuroanatomy. Using multi-shell diffusion images of 56 subjects from Human Connectome Project,we compare our method with algorithms from MRtrix. By applying regression analysis between retinotopic eccentricity and tracks,we quantitatively demonstrate that our method achieves superior performance in preserving the retinotopic organization of optic radiation.

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
TilaJulkaistu - 1 tammikuuta 2016
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Workshop on Simulation and Synthesis in Medical Imaging - Athens, Kreikka
Kesto: 21 lokakuuta 201621 lokakuuta 2016
Konferenssinumero: 1

Julkaisusarja

NimiLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vuosikerta9900 LNCS
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Workshop

WorkshopInternational Workshop on Simulation and Synthesis in Medical Imaging
LyhennettäSASHIMI
MaaKreikka
KaupunkiAthens
Ajanjakso21/10/201621/10/2016

ID: 29135066