Automatic segmentation of brain tissue based on improvedfuzzy c means clustering algorithm
Open Access
- 1 January 2011
- journal article
- Published by Scientific Research Publishing, Inc. in Journal of Biomedical Science and Engineering
- Vol. 04 (02), 100-104
- https://doi.org/10.4236/jbise.2011.42014
Abstract
In medical images, exist often a lot of noise, the noise will seriously affect the accuracy of the segmentation results. The traditional standard fuzzy c-means(FCM) algorithm in image segmentation do not taken into account the relationship the adjacent pixels, which leads to the standard fuzzy c-means(FCM) algorithm is very sensitive to noise in the image. Proposed improvedfuzzy c-means(FCM) algorithm, taking both the local and non-local information into the standard fuzzy c-means(FCM) clustering algorithm. The ex-periment results can show that the improved algorithm can achieve better effect than other methods of brain tissue segmentationKeywords
This publication has 1 reference indexed in Scilit:
- A Convergence Theorem for the Fuzzy ISODATA Clustering AlgorithmsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1980