Mri Image Segmentation Based on FCM Clustering Using an Adaptive Threshold Algorithm


Using thresholding method to segment an image, a fixed threshold is not suitable if the background is rough Here, we propose a new adaptive thresholding method using FCM. The method requires only one parameter to be selected and the adaptive threshold surface can be found automatically from the original image.An adaptive thresholding scheme using adaptive tracking and morphological filtering. FCM algorithm computes the fuzzy membership values for each pixel. Our method is good for detecting large and small images concurrently. It is also efficient to denoise and enhance the responses of images with low local contrast can be detected. The efficiency and accuracy of the algorithm is demonstrated by the experiments on the MR brain images.

  • Abstract
  • Key Words
  • 1. Introduction
  • 2. Adaptive Thresholding
  • 3. Fuzzy C-Means Clustering (FCM):
  • 4. Experimental Results
  • 5. Discussions
  • 6. Conclusions
  • References

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In