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Mri Image Segmentation Based on FCM Clustering Using an Adaptive Threshold Algorithm
- Publication Year :
- 2011
- Publisher :
- ASME Press, 2011.
-
Abstract
- 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.
- Subjects :
- Mri image
Fcm clustering
Computer science
business.industry
Segmentation-based object categorization
Computer Science::Computer Vision and Pattern Recognition
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Scale-space segmentation
Segmentation
Pattern recognition
Artificial intelligence
Image segmentation
business
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi...........0f7b3ba2ada7a0edd6c3a94ff0a99871