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## Performance Analysis of Fuzzy Competitive Learning Algorithms for MR Image Segmentation

### Citations

2068 | Pattern Recognition with Fuzzy Objective Function Algorithms - Bezdek - 1981 |

1367 | Fuzzy sets and fuzzy logic, theory and applications - Klir, Yuan - 1995 |

436 |
A universal image quality index,”
- Wang, Bovik
- 2002
(Show Context)
Citation Context ...– No.8, May 2013 measures the structural distortion rather than the error and is easy to calculate and applicable to various image processing applications. The image quality index (IQI) is defined as =-=[16]-=-: Q � 4� xy xy 2 2 ��x �� � y � � x���y� �� 2 2 Where, x = {x i | i=1, 2… N}, and y = {y i | i =1, 2… N} are the original and the test image (segmented image) signals, respectively and N is the total ... |

150 |
Mean squared error: love it or leave it? A new look at signal fidelity measures,
- Wang, Bovik
- 2009
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Citation Context ...an original signal of acceptable quality, and the other is a segmented image of it whose quality is being evaluated, then MSE may also be regarded as a measure of image quality. The MSE is defined as =-=[15]-=-: N 1 MSE( x, y) � � � xi � yi N i�1 Where, x = {x i | i=1, 2… N}, and y = {y i | i = 1, 2… N} are the original and the test image (segmented image) signals, respectively and N is the total number of ... |

81 | A survey of fuzzy clustering algorithms for pattern recognition
- Baraldi, Blonda
- 1999
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Citation Context ...f membership and (iii) its capability of drawing approximate inferences. Fuzzy set theory help to transfer a qualitative evaluation of the medical data into the algorithmic structure. Baraldi et al., =-=[10]-=-, [11] present a survey on fuzzy clustering algorithms for pattern recognition. Literature survey shows that many fuzzy clustering algorithms aim to model fuzzy (i.e., ambiguous) unsupervised (unlabel... |

33 |
Parallel self-organizing feature maps for unsupervised pattern recognition
- Huntsberger, Ajjimarangsee
- 1989
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Citation Context ...Q) can reduce this sensitivity of parameters. It provides a subsequent link between batch FCM and LVQ and also overcomes the problems in LVQ. This was first discussed by Huntsberger and Ajjimarangsee =-=[8]-=-. The FLVQ is more suitable than GKCL-based algorithms in comparison and gained a successful batch clustering algorithm that is applied in MRI. Further, another modified batch clustering learning meth... |

14 |
Comparing som neural network with fuzzy c-means, k-means and traditional hierarchical clustering algorithms.
- Mingoti, Lima
- 2006
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Citation Context ...FSLVQ)) have been developed to improve performance and usability [3-6]. The KCL is a sequemtial type and the LVQ is a batch type. LVQ is a simplest case for self organizing map (SOM). Mingoti et al., =-=[7]-=- present a comparison of SOM neural network, fuzzy cmean, k-means and hierarchical clustering algorithms. Based on the comparison it is found that fuzzy c- mean clustering algorithm performed well in ... |

2 |
Pattern Recognition for Medical imaging
- Base
- 2004
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Citation Context ...ntegration of these two paradigms thus enhancing their individual capabilities. MRI is a medical imaging technique that uses nuclear magnetic resonance of protons to produce proton density images [1] =-=[2]-=-. The image pixel value can be considered as subsets of parameters including the time constants characterization T1 (magnetization vector along with longitudinal axis) and T2 (transverse component) an... |

1 | Raghu Krisnapuram and Nikhil - Bezdek, Keller - 2005 |

1 |
Jiing-Feng Lirng and Pei-Ning Wang, “Generalized Kohonen’s competitive learning algorithms for opthalmological MR image segmentation”, Magnetic Resonance Imaging 21
- Lin, Yang, et al.
- 2003
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Citation Context ...ions than any other algorithms. LVQ attempts to update only the winning prototype, generalization of LVQ-fuzzy variant is developed to updates all the c-prototypes with the learning rule. Lin et al., =-=[4]-=- proposed a generalized Kohonen’s competitive learning (GKCL) for MR image segmentation called fuzzy KCL (FKCL) and fuzzy soft KCL (FSKCL) and is successfully applied to two actual ophthalmology cases... |

1 |
Hsui-Chih Liu and Jiing-Feng Lirng, “Magnetic resonance imaging segmentation techniques using batch-type learning vector quantization algorithms. Magnetic Resonance Imaging 25
- yang, Lin
- 2007
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Citation Context ...ft learning vector quantization (FSLVQ) is proposed in Wu et al., [4] and produce better performance than the FLVQ in comparison but it is tested with numerical data only. Based on this, Yang et al., =-=[5]-=- proposed the FSLVQ segmentation technique with MRI and it works well on Alzheimer disease (AD) MRI. The tested results of the FSLVQ are compared with the other LVQ-based and GKCLbased algorithms and ... |

1 | A fuzzy-soft learning vector quantization’, Nurocomputing 55 - Wu, Yang - 2003 |

1 |
Review Article, Fuzzy Logic in Medicine and Bioinformatics
- Angela, Neito
- 2006
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Citation Context ...agueness and incompleteness in medical diagnosis and prognosis. It can be used to represent fuzzy objects (both linguistic and/or set of variables) and fuzzy logic (reasoning methods). Torres et al., =-=[9]-=- presents a review on the current applications of fuzzy logic in medicine and bioinformatics. The main reasons for the application of fuzzy set theory in pattern recognition are: (i) its way of repres... |