Non-uniform gradient prescription for precise angular measurements using DTI.

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Diffusion Tensor Imaging (DTI) calculates a tensor for each voxel, representing the mean diffusive characteristics in volume-averaged tissue. Gradients that phase-encode spins according to the amount of their diffusion are usually applied uniformly over a sphere during a DTI procedure for minimal bias of tensor information. If prior knowledge of diffusion direction exists, the angular precision for determining the principle eigenvector of cylindrically-symmetric ("prolate") tensors can be improved by specifying gradients non-uniformly. Improvements in precision of 30-40% can be achieved using a restricted band of zenith angle values for gradient directions. Sensitivity to the a priori angular range of the principle eigenvector can be adjusted with the width of the band. Simulations and phantom data are in agreement; a preliminary validation is presented.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages866-873
Number of pages8
Volume11
EditionPt 1
DOIs
StatePublished - Dec 1 2008
Event11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008 - New York, NY, United States
Duration: Sep 6 2008Sep 10 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5241 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008
CountryUnited States
CityNew York, NY
Period9/6/089/10/08

Fingerprint

Diffusion tensor imaging
Angle measurement
Tensors
Tensor
Imaging
Gradient
Eigenvalues and eigenfunctions
Eigenvector
Tissue
Voxel
Phantom
Prior Knowledge
Angle
Calculate
Range of data
Simulation

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Yanasak, N., Allison, J. D., Zhao, Q., Hu, T. C. C., & Dhandapani, K. (2008). Non-uniform gradient prescription for precise angular measurements using DTI. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 1 ed., Vol. 11, pp. 866-873). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5241 LNCS, No. PART 1). https://doi.org/10.1007/978-3-540-85988-8_103

Non-uniform gradient prescription for precise angular measurements using DTI. / Yanasak, Nathan; Allison, Jerry D.; Zhao, Qun; Hu, Tom C C; Dhandapani, Krishnan.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 11 Pt 1. ed. 2008. p. 866-873 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5241 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingChapter

Yanasak, N, Allison, JD, Zhao, Q, Hu, TCC & Dhandapani, K 2008, Non-uniform gradient prescription for precise angular measurements using DTI. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 edn, vol. 11, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5241 LNCS, pp. 866-873, 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008, New York, NY, United States, 9/6/08. https://doi.org/10.1007/978-3-540-85988-8_103
Yanasak N, Allison JD, Zhao Q, Hu TCC, Dhandapani K. Non-uniform gradient prescription for precise angular measurements using DTI. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 ed. Vol. 11. 2008. p. 866-873. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-540-85988-8_103
Yanasak, Nathan ; Allison, Jerry D. ; Zhao, Qun ; Hu, Tom C C ; Dhandapani, Krishnan. / Non-uniform gradient prescription for precise angular measurements using DTI. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 11 Pt 1. ed. 2008. pp. 866-873 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
@inbook{efeaa8d8aee44840b6f808c8d93b41df,
title = "Non-uniform gradient prescription for precise angular measurements using DTI.",
abstract = "Diffusion Tensor Imaging (DTI) calculates a tensor for each voxel, representing the mean diffusive characteristics in volume-averaged tissue. Gradients that phase-encode spins according to the amount of their diffusion are usually applied uniformly over a sphere during a DTI procedure for minimal bias of tensor information. If prior knowledge of diffusion direction exists, the angular precision for determining the principle eigenvector of cylindrically-symmetric ({"}prolate{"}) tensors can be improved by specifying gradients non-uniformly. Improvements in precision of 30-40{\%} can be achieved using a restricted band of zenith angle values for gradient directions. Sensitivity to the a priori angular range of the principle eigenvector can be adjusted with the width of the band. Simulations and phantom data are in agreement; a preliminary validation is presented.",
author = "Nathan Yanasak and Allison, {Jerry D.} and Qun Zhao and Hu, {Tom C C} and Krishnan Dhandapani",
year = "2008",
month = "12",
day = "1",
doi = "10.1007/978-3-540-85988-8_103",
language = "English (US)",
isbn = "354085987X",
volume = "11",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "866--873",
booktitle = "Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention",
edition = "Pt 1",

}

TY - CHAP

T1 - Non-uniform gradient prescription for precise angular measurements using DTI.

AU - Yanasak, Nathan

AU - Allison, Jerry D.

AU - Zhao, Qun

AU - Hu, Tom C C

AU - Dhandapani, Krishnan

PY - 2008/12/1

Y1 - 2008/12/1

N2 - Diffusion Tensor Imaging (DTI) calculates a tensor for each voxel, representing the mean diffusive characteristics in volume-averaged tissue. Gradients that phase-encode spins according to the amount of their diffusion are usually applied uniformly over a sphere during a DTI procedure for minimal bias of tensor information. If prior knowledge of diffusion direction exists, the angular precision for determining the principle eigenvector of cylindrically-symmetric ("prolate") tensors can be improved by specifying gradients non-uniformly. Improvements in precision of 30-40% can be achieved using a restricted band of zenith angle values for gradient directions. Sensitivity to the a priori angular range of the principle eigenvector can be adjusted with the width of the band. Simulations and phantom data are in agreement; a preliminary validation is presented.

AB - Diffusion Tensor Imaging (DTI) calculates a tensor for each voxel, representing the mean diffusive characteristics in volume-averaged tissue. Gradients that phase-encode spins according to the amount of their diffusion are usually applied uniformly over a sphere during a DTI procedure for minimal bias of tensor information. If prior knowledge of diffusion direction exists, the angular precision for determining the principle eigenvector of cylindrically-symmetric ("prolate") tensors can be improved by specifying gradients non-uniformly. Improvements in precision of 30-40% can be achieved using a restricted band of zenith angle values for gradient directions. Sensitivity to the a priori angular range of the principle eigenvector can be adjusted with the width of the band. Simulations and phantom data are in agreement; a preliminary validation is presented.

UR - http://www.scopus.com/inward/record.url?scp=58849086830&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=58849086830&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-85988-8_103

DO - 10.1007/978-3-540-85988-8_103

M3 - Chapter

C2 - 18979827

SN - 354085987X

SN - 9783540859871

VL - 11

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

SP - 866

EP - 873

BT - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

ER -