Belief propagation based segmentation of white matter tracts in DTI

Pierre Louis Bazin, John Bogovic, Daniel Reich, Jerry L. Prince, Dzung L. Pham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a belief propagation approach to the segmentation of the major white matter tracts in diffusion tensor images of the human brain. Unlike tractography methods that sample multiple fibers to be bundled together, we define a Markov field directly on the diffusion tensors to separate the main fiber tracts at the voxel level. A prior model of shape and direction guides a full segmentation of the brain into known fiber tracts; additional, unspecified fibers; and isotropic regions. The method is evaluated on various data sets from an atlasing project, healthy subjects, and multiple sclerosis patients.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages943-950
Number of pages8
Volume5761 LNCS
EditionPART 1
DOIs
StatePublished - 2009
Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
Duration: Sep 20 2009Sep 24 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5761 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
CountryUnited Kingdom
CityLondon
Period9/20/099/24/09

Fingerprint

Belief Propagation
Segmentation
Fiber
Fibers
Tensors
Brain
Tensor
Multiple Sclerosis
Voxel
Model

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Bazin, P. L., Bogovic, J., Reich, D., Prince, J. L., & Pham, D. L. (2009). Belief propagation based segmentation of white matter tracts in DTI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 5761 LNCS, pp. 943-950). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5761 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-04268-3_116

Belief propagation based segmentation of white matter tracts in DTI. / Bazin, Pierre Louis; Bogovic, John; Reich, Daniel; Prince, Jerry L.; Pham, Dzung L.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5761 LNCS PART 1. ed. 2009. p. 943-950 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5761 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bazin, PL, Bogovic, J, Reich, D, Prince, JL & Pham, DL 2009, Belief propagation based segmentation of white matter tracts in DTI. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 5761 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5761 LNCS, pp. 943-950, 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, London, United Kingdom, 9/20/09. https://doi.org/10.1007/978-3-642-04268-3_116
Bazin PL, Bogovic J, Reich D, Prince JL, Pham DL. Belief propagation based segmentation of white matter tracts in DTI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 5761 LNCS. 2009. p. 943-950. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-04268-3_116
Bazin, Pierre Louis ; Bogovic, John ; Reich, Daniel ; Prince, Jerry L. ; Pham, Dzung L. / Belief propagation based segmentation of white matter tracts in DTI. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5761 LNCS PART 1. ed. 2009. pp. 943-950 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
@inproceedings{f42724b38d5e4b3db23a6ceb8235311e,
title = "Belief propagation based segmentation of white matter tracts in DTI",
abstract = "This paper presents a belief propagation approach to the segmentation of the major white matter tracts in diffusion tensor images of the human brain. Unlike tractography methods that sample multiple fibers to be bundled together, we define a Markov field directly on the diffusion tensors to separate the main fiber tracts at the voxel level. A prior model of shape and direction guides a full segmentation of the brain into known fiber tracts; additional, unspecified fibers; and isotropic regions. The method is evaluated on various data sets from an atlasing project, healthy subjects, and multiple sclerosis patients.",
author = "Bazin, {Pierre Louis} and John Bogovic and Daniel Reich and Prince, {Jerry L.} and Pham, {Dzung L.}",
year = "2009",
doi = "10.1007/978-3-642-04268-3_116",
language = "English (US)",
isbn = "3642042678",
volume = "5761 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "943--950",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
edition = "PART 1",

}

TY - GEN

T1 - Belief propagation based segmentation of white matter tracts in DTI

AU - Bazin, Pierre Louis

AU - Bogovic, John

AU - Reich, Daniel

AU - Prince, Jerry L.

AU - Pham, Dzung L.

PY - 2009

Y1 - 2009

N2 - This paper presents a belief propagation approach to the segmentation of the major white matter tracts in diffusion tensor images of the human brain. Unlike tractography methods that sample multiple fibers to be bundled together, we define a Markov field directly on the diffusion tensors to separate the main fiber tracts at the voxel level. A prior model of shape and direction guides a full segmentation of the brain into known fiber tracts; additional, unspecified fibers; and isotropic regions. The method is evaluated on various data sets from an atlasing project, healthy subjects, and multiple sclerosis patients.

AB - This paper presents a belief propagation approach to the segmentation of the major white matter tracts in diffusion tensor images of the human brain. Unlike tractography methods that sample multiple fibers to be bundled together, we define a Markov field directly on the diffusion tensors to separate the main fiber tracts at the voxel level. A prior model of shape and direction guides a full segmentation of the brain into known fiber tracts; additional, unspecified fibers; and isotropic regions. The method is evaluated on various data sets from an atlasing project, healthy subjects, and multiple sclerosis patients.

UR - http://www.scopus.com/inward/record.url?scp=77952277978&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77952277978&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-04268-3_116

DO - 10.1007/978-3-642-04268-3_116

M3 - Conference contribution

SN - 3642042678

SN - 9783642042676

VL - 5761 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 943

EP - 950

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -