Robust brain registration using adaptive probabilistic atlas

Jaime Ide, Rong Chen, Dinggang Shen, Edward H. Herskovits

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

2 Citations (Scopus)


Elastic image registration is widely used to adapt brain images to a common template space, and, in complementary fashion, to adapt an anatomical template to a subject's anatomy. Although HAMMER is a very accurate image-registration algorithm, it requires a 3-class segmentation step prior to registration, and its performance is affected by segmentation quality. We here propose a new framework to improve this algorithm's robustness to poor initial segmentation. Our new framework is based on Adaptive Generalized Expectation Maximization (AGEM) for unified segmentation and registration, in which we use an adaptive strategy to incorporate spatial information from a probabilistic atlas to improve segmentation and registration simultaneously. Our experiments using real MR brain images indicate that our integrated approach improves registration accuracy; we have also found that our iterative approach renders HAMMER robust to low tissue contrast, which hinders 3-class segmentation.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2008 - 11th International Conference, Proceedings
PublisherSpringer Verlag
Number of pages9
EditionPART 2
ISBN (Print)3540859896, 9783540859895
Publication statusPublished - 2008
Event11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008 - New York, NY, United States
Duration: 2008 Sept 62008 Sept 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5242 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008
Country/TerritoryUnited States
CityNew York, NY

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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