Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction

Rick Archibald, Jiuxiang Hu, Anne Gelb, Gerald Farin

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

The concentration edge -detection and Gegenbauer image-reconstruction methods were previously shown to improve the quality of segmentation in magnetic resonance imaging. In this study, these methods are utilized as a pre-processing step to the Weibull E-SD field segmentation. It is demonstrated that the combination of the concentration edge detection and Gegenbauer reconstruction method improves the accuracy of segmentation for the simulated test data and real magnetic resonance images used in this study.

Original languageEnglish (US)
Pages (from-to)459-466
Number of pages8
JournalIEEE Transactions on Image Processing
Volume13
Issue number4
DOIs
StatePublished - Apr 2004

Fingerprint

Boundary Detection
Edge detection
Image Reconstruction
Magnetic resonance
Image reconstruction
Preprocessing
Segmentation
Edge Detection
Processing
Magnetic Resonance Image
Magnetic Resonance Imaging
Weibull
Imaging techniques

Keywords

  • Edge detection
  • Gegenbauer reconstruction
  • Magnetic resonance imaging
  • Three dimensional (3-D) segmentation
  • Weibull E-SD field

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Cite this

Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction. / Archibald, Rick; Hu, Jiuxiang; Gelb, Anne; Farin, Gerald.

In: IEEE Transactions on Image Processing, Vol. 13, No. 4, 04.2004, p. 459-466.

Research output: Contribution to journalArticle

Archibald, Rick ; Hu, Jiuxiang ; Gelb, Anne ; Farin, Gerald. / Improving the accuracy of volumetric segmentation using pre-processing boundary detection and image reconstruction. In: IEEE Transactions on Image Processing. 2004 ; Vol. 13, No. 4. pp. 459-466.
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