Statistical shape model for automatic skull-stripping of brain images

Zhiqiang Lao, Dinggang Shen, Christos Davatzikos

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

6 Citations (Scopus)


This paper presents a statistical shape model for automatic skull stripping of MR brain images. A surface model of the brain boundary is hierarchically represented by a set of overlapping surface patches, each of which has elastic properties and deformation range that is learned from a training set. The model's deformation is hierarchical which adds robustness to local minima. Moreover, the deformation of the model is constrained and guided by global shape statistics. The model is deformed to the brain boundary by a procedure that matches the local image structures and evaluates the similarity in the whole patch rather than on a single vertex. The experimental results show high agreement between automatic and supervised skull-stripping results.

Original languageEnglish
Title of host publicationProceedings - International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)078037584X
Publication statusPublished - 2002
Externally publishedYes
EventIEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States
Duration: 2002 Jul 72002 Jul 10


OtherIEEE International Symposium on Biomedical Imaging, ISBI 2002
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


Dive into the research topics of 'Statistical shape model for automatic skull-stripping of brain images'. Together they form a unique fingerprint.

Cite this