Adaptive FCM with contextual constrains for segmentation of multi-spectral MRI

Renjie He, Sushmita Datta, Balasrinivasa Rao Sajja, Meghana Mehta, Ponnada A. Narayana

Research output: Contribution to journalConference article

16 Scopus citations

Abstract

An adaptive fuzzy c-means (FCM) clustering algorithm is explored for segmentation of three-dimensional multi-spectral MR images. This algorithm takes into consideration of both noise and three-dimensional intensity non-uniformity. This algorithm models the intensity non-uniformity of MR images as a gain field or bias field that slowly varies in space, which is approximated by a linear combination of smooth basis functions made up of polynomials with different orders. The contextual constraints are included by introducing a regularization term into the cost function of FCM. The regularization term is a measure of aggregation of local voxels that tend to overcome the noise in voxel labeling. We present our scheme both for bias and gain fields, with special attention is paid to robust estimation of the bias field.

Original languageEnglish (US)
Pages (from-to)1660-1663
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume26 III
StatePublished - 2004
EventConference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States
Duration: Sep 1 2004Sep 5 2004

Keywords

  • Adaptive
  • Bias field
  • Contextual Constraints
  • FCM
  • MRI
  • Multi-spectral
  • Segmentation

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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