ITree: Fast and accurate image registration based on the combinative and incremental tree

Hongjun Jia, Guorong Wu, Qian Wang, Minjeong Kim, Dinggang Shen

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

6 Citations (Scopus)

Abstract

In this paper, a novel tree-based registration framework is proposed for achieving fast and accurate registration by providing a more appropriate initial deformation field for the image under registration. Specifically, in the training stage, all training real images and a selected portion of simulated images are organized into a combinative tree with the template as the root, and then each training image is registered to the template with the guidance from the intermediate images on its path to the template. In the testing stage, for a given new image, we first attach it as a child node of its most similar image on the tree, and then use the respective deformation field of this image to initialize the registration. In this way, the residual deformation of the new image to the template can be fast and robustly estimated. In the other case, to register a set of new images, we attach them to the tree one by one by allowing similar test images to help each other during the registration. Importantly, after registration of all new images, a new tree is built which is more capable of representing population distribution and thus allowing for better and faster registration for new future images. This method has been evaluated on the real brain MR image datasets, showing that it can achieve better accuracy within less time than both the statistical model based registration method and the tree-based registration method.

Original languageEnglish
Title of host publication2011 8th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI'11
Pages1243-1246
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States
Duration: 2011 Mar 302011 Apr 2

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

Other2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
CountryUnited States
CityChicago, IL
Period11/3/3011/4/2

Keywords

  • Image registration
  • combinative tree
  • incremental tree
  • intermediate template
  • statistical model

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Jia, H., Wu, G., Wang, Q., Kim, M., & Shen, D. (2011). ITree: Fast and accurate image registration based on the combinative and incremental tree. In 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 (pp. 1243-1246). [5872627] (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2011.5872627