Dynamic tree-based large-deformation image registration for multi-atlas segmentation

Pei Zhang, Guorong Wu, Yaozong Gao, Pew Thian Yap, Dinggang Shen

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

1 Citation (Scopus)


Multi-atlas segmentation is a powerful approach to automated anatomy delineation via fusing label information from a set of spatially normalized atlases. For simplicity, many existing methods perform pairwise image registration, leading to inaccurate segmentation especially when shape variation is large. In this paper, we propose a dynamic tree-based strategy for effective large-deformation registration and multiatlas segmentation. To deal with local minima caused by large shape variation, coarse estimates of deformations are first obtained via alignment of automatically localized landmark points. A dynamic tree capturing the structural relationships between images is then used to further reduce misalignment errors. Validation on two real human brain datasets, ADNI and LPBA40, shows that our method significantly improves registration and segmentation accuracy.

Original languageEnglish
Title of host publicationMedical Computer Vision
Subtitle of host publicationAlgorithms for Big Data - International Workshop, MCV 2015 and Held in Conjunction with MICCAI 2015, Revised Selected Papers
EditorsMichael Kelm, Henning Müller, Bjoern Menze, Shaoting Zhang, Dimitris Metaxas, Georg Langs, Albert Montillo, Weidong Cai
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783319420158
Publication statusPublished - 2016
Externally publishedYes
EventInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI - Germany, Germany
Duration: 2015 Oct 92015 Oct 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9601 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Workshop on Medical Image Computing for Computer Assisted Intervention, 2015 MICCAI

Bibliographical note

Funding Information:
This work was supported in part by a UNC BRIC-Radiology start-up fund, and NIH grants (EB006733, EB008374, EB009634, MH088520 and NIHM 5R01MH091645-02)

Publisher Copyright:
© Springer International Publishing Switzerland 2016.

Copyright 2017 Elsevier B.V., All rights reserved.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Dynamic tree-based large-deformation image registration for multi-atlas segmentation'. Together they form a unique fingerprint.

Cite this