Regularized shape deformation for image segmentation

S. Wang, Zhi-Pei Liang

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper presents a new method for image segmentation by deforming the object shape in a template. The deformation process is controlled using a thin-plate spline kernel based regularization method. The proposed method is especially useful for 2D-based segmentation of 3D medical images by treating segmented slices. We have applied the proposed method to extract the scalp contours in brain cryosection images with very encouraging results.

Original languageEnglish (US)
Pages (from-to)1569-1572
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume3
StatePublished - 2001
Event2001 IEEE International Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States
Duration: May 7 2001May 11 2001

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Regularized shape deformation for image segmentation'. Together they form a unique fingerprint.

Cite this