Deformable registration of cortical structures via hybrid volumetric and surface warping

Tianming Liu, Dinggang Shen, Christos Davatzikos

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

Abstract

This paper presents a method of deformable registration of cortical structures across individuals, using hybrid volumetric and surface warping. The proposed method uses two steps. In the first step, a HAMMER-based volumetric registration algorithm warps the model surface to the individual's space. In the second step, an attribute-based surface registration method further refines the results of the volumetric warping. An attribute vector is defined for each vertex on the cortical surface, and used to capture the local and global geometric features of the surface patch. The attribute vector is designed to be as distinctive as possible, so that each vertex on the model surface can find its correspondence on the individual surface. Experimental results on synthesized and real brain data are provided to demonstrate the performance of the proposed method in registering cortical structures across individuals.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science
EditorsR.E. Ellis, T.M. Peters
Pages780-787
Number of pages8
Volume2879
EditionPART 2
StatePublished - 2003
Externally publishedYes
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada
Duration: Nov 15 2003Nov 18 2003

Other

OtherMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings
CountryCanada
CityMontreal, Que.
Period11/15/0311/18/03

Fingerprint

Warping
Registration
Attribute
Vertex of a graph
Patch
Brain
Correspondence
Experimental Results
Model
Demonstrate

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Engineering(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Liu, T., Shen, D., & Davatzikos, C. (2003). Deformable registration of cortical structures via hybrid volumetric and surface warping. In R. E. Ellis, & T. M. Peters (Eds.), Lecture Notes in Computer Science (PART 2 ed., Vol. 2879, pp. 780-787)

Deformable registration of cortical structures via hybrid volumetric and surface warping. / Liu, Tianming; Shen, Dinggang; Davatzikos, Christos.

Lecture Notes in Computer Science. ed. / R.E. Ellis; T.M. Peters. Vol. 2879 PART 2. ed. 2003. p. 780-787.

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

Liu, T, Shen, D & Davatzikos, C 2003, Deformable registration of cortical structures via hybrid volumetric and surface warping. in RE Ellis & TM Peters (eds), Lecture Notes in Computer Science. PART 2 edn, vol. 2879, pp. 780-787, Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings, Montreal, Que., Canada, 11/15/03.
Liu T, Shen D, Davatzikos C. Deformable registration of cortical structures via hybrid volumetric and surface warping. In Ellis RE, Peters TM, editors, Lecture Notes in Computer Science. PART 2 ed. Vol. 2879. 2003. p. 780-787
Liu, Tianming ; Shen, Dinggang ; Davatzikos, Christos. / Deformable registration of cortical structures via hybrid volumetric and surface warping. Lecture Notes in Computer Science. editor / R.E. Ellis ; T.M. Peters. Vol. 2879 PART 2. ed. 2003. pp. 780-787
@inproceedings{b9b55688496e4d4092187084449e117c,
title = "Deformable registration of cortical structures via hybrid volumetric and surface warping",
abstract = "This paper presents a method of deformable registration of cortical structures across individuals, using hybrid volumetric and surface warping. The proposed method uses two steps. In the first step, a HAMMER-based volumetric registration algorithm warps the model surface to the individual's space. In the second step, an attribute-based surface registration method further refines the results of the volumetric warping. An attribute vector is defined for each vertex on the cortical surface, and used to capture the local and global geometric features of the surface patch. The attribute vector is designed to be as distinctive as possible, so that each vertex on the model surface can find its correspondence on the individual surface. Experimental results on synthesized and real brain data are provided to demonstrate the performance of the proposed method in registering cortical structures across individuals.",
author = "Tianming Liu and Dinggang Shen and Christos Davatzikos",
year = "2003",
language = "English (US)",
volume = "2879",
pages = "780--787",
editor = "R.E. Ellis and T.M. Peters",
booktitle = "Lecture Notes in Computer Science",
edition = "PART 2",

}

TY - GEN

T1 - Deformable registration of cortical structures via hybrid volumetric and surface warping

AU - Liu, Tianming

AU - Shen, Dinggang

AU - Davatzikos, Christos

PY - 2003

Y1 - 2003

N2 - This paper presents a method of deformable registration of cortical structures across individuals, using hybrid volumetric and surface warping. The proposed method uses two steps. In the first step, a HAMMER-based volumetric registration algorithm warps the model surface to the individual's space. In the second step, an attribute-based surface registration method further refines the results of the volumetric warping. An attribute vector is defined for each vertex on the cortical surface, and used to capture the local and global geometric features of the surface patch. The attribute vector is designed to be as distinctive as possible, so that each vertex on the model surface can find its correspondence on the individual surface. Experimental results on synthesized and real brain data are provided to demonstrate the performance of the proposed method in registering cortical structures across individuals.

AB - This paper presents a method of deformable registration of cortical structures across individuals, using hybrid volumetric and surface warping. The proposed method uses two steps. In the first step, a HAMMER-based volumetric registration algorithm warps the model surface to the individual's space. In the second step, an attribute-based surface registration method further refines the results of the volumetric warping. An attribute vector is defined for each vertex on the cortical surface, and used to capture the local and global geometric features of the surface patch. The attribute vector is designed to be as distinctive as possible, so that each vertex on the model surface can find its correspondence on the individual surface. Experimental results on synthesized and real brain data are provided to demonstrate the performance of the proposed method in registering cortical structures across individuals.

UR - http://www.scopus.com/inward/record.url?scp=11244343024&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=11244343024&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:11244343024

VL - 2879

SP - 780

EP - 787

BT - Lecture Notes in Computer Science

A2 - Ellis, R.E.

A2 - Peters, T.M.

ER -