A Modified Fuzzy Kohonen's Competitive Learning Algorithms Incorporating Local Information for MR Image Segmentation

A modified FKCL (MFKCL) algorithm for automatic segmentation of MR brain images is proposed in this paper. This algorithm is an extension of traditional fuzzy Kohonen's competitive learning algorithm. In our method, a factor that can estimate the effect of the neighbor pixels to the central pix...

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Bibliographic Details
Main Authors: Kong, Jun, Lu, Wenjing, Wang, Jianzhong, Che, Na, Lu, Yinghua
Format: Conference Proceeding
Language:English
Subjects:
Biomedical imaging
Clustering algorithms
Clustering methods
Image segmentation
Laboratories
Magnetic resonance
Magnetic resonance imaging
Medical diagnostic imaging
Noise reduction
Tomography
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Summary:A modified FKCL (MFKCL) algorithm for automatic segmentation of MR brain images is proposed in this paper. This algorithm is an extension of traditional fuzzy Kohonen's competitive learning algorithm. In our method, a factor that can estimate the effect of the neighbor pixels to the central pixel is introduced into the objective function of the standard FKCL algorithm as the local information. The local information is applied to trail off the effect of noise to the result of MRI segmentation. Experiments with simulated MR data and real MR data show that our algorithm can resist not only the little, but also the heavy noise compared with standard FKCL segmentation and other reported methods.
DOI:10.1109/BIBE.2007.4375629