Adaptive-focus statistical shape model for segmentation of 3D MR structures

Dinggang Shen, Christos Davatzikos

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

9 Citations (Scopus)

Abstract

This paper presents a deformable model for automatically segmenting objects from volumetric MR images and obtaining point correspondences, using geometric and statistical information in a hierarchical scheme. Geometric information is embedded into the model via an affine-invariant attribute vector, which characterizes the geometric structure around each model point from a local to a global level. Accordingly, the model deforms seeking boundary points with similar attribute vectors. This is in contrast to most deformable surface models, which adapt to nearby edges without considering the geometric structure. The proposed model is adaptive in that it initially focuses on the most reliable structures of interest, and subsequently switches focus to other structures as those become closer to their respective targets and therefore more reliable. The proposed techniques have been used to segment boundaries of the ventricles, the caudate nucleus, and the lenticular nucleus from volumetric MR images.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages206-215
Number of pages10
Volume1935
ISBN (Print)3540411895, 9783540411895
Publication statusPublished - 2000
Externally publishedYes
Event3rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2000 - Pittsburgh, United States
Duration: 2000 Oct 112000 Oct 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1935
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2000
CountryUnited States
CityPittsburgh
Period00/10/1100/10/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Shen, D., & Davatzikos, C. (2000). Adaptive-focus statistical shape model for segmentation of 3D MR structures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1935, pp. 206-215). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1935). Springer Verlag.