Journal ArticleDOI
Improved spatial fuzzy c-means clustering for image segmentation using PSO initialization, Mahalanobis distance and post-segmentation correction
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TLDR
The proposed improvement method, named improved spatial fuzzy c-means IFCMS, was evaluated on several test images including both synthetic images and simulated brain MRI images from the McConnell Brain Imaging Center (BrainWeb) database and demonstrates the efficiency of the ideas presented.About:
This article is published in Digital Signal Processing.The article was published on 2013-09-01. It has received 137 citations till now. The article focuses on the topics: Scale-space segmentation & Segmentation-based object categorization.read more
Citations
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Journal ArticleDOI
A review on brain tumor segmentation of MRI images.
TL;DR: Through the entire review process, it has been observed that the combination of Conditional Random Field (CRF) with Fully Convolutional Neural Network (FCNN) and CRF with DeepMedic or Ensemble are more effective for the segmentation of tumor from the brain MRI images.
Journal ArticleDOI
Conditional spatial fuzzy C-means clustering algorithm for segmentation of MRI images
TL;DR: The experimental results show that the csFCM algorithm has superior performance in terms of qualitative and quantitative studies such as, cluster validity functions, segmentation accuracy, tissue segmentsation accuracy and receiver operating characteristic (ROC) curve on the image segmentation results than the k-means, FCM and some other recently proposed FCM-based algorithms.
Journal ArticleDOI
A fuzzy clustering segmentation method based on neighborhood grayscale information for defining cucumber leaf spot disease images
TL;DR: The proposed segmentation method provides an effective and robust segmentation means for sorting and grading apples in cucumber disease diagnosis, and it can be easily adapted for other imaging-based agricultural applications.
Journal ArticleDOI
State-of-the-Art Methods for Brain Tissue Segmentation: A Review
TL;DR: The brain tissue segmentation, content in terms of methodologies, and experiments presented in this review are encouraging enough to attract researchers working in this field.
Journal ArticleDOI
Retinal Blood Vessel Segmentation by Using Matched Filtering and Fuzzy C-means Clustering with Integrated Level Set Method for Diabetic Retinopathy Assessment
Nogol Memari,Abd Rahman Ramli,M. Iqbal Saripan,Syamsiah Mashohor,Mehrdad Moghbel,Mehrdad Moghbel +5 more
TL;DR: The proposed retinal vessel segmentation method was able to achieve comparable accuracy to other methods while being very close to the manual segmentation provided by the second observer in all datasets.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
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Pattern Recognition with Fuzzy Objective Function Algorithms
TL;DR: Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.
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The particle swarm optimization algorithm: convergence analysis and parameter selection
TL;DR: The particle swarm optimization algorithm is analyzed using standard results from the dynamic system theory and graphical parameter selection guidelines are derived, resulting in results superior to previously published results.
Journal ArticleDOI
A possibilistic approach to clustering
TL;DR: An appropriate objective function whose minimum will characterize a good possibilistic partition of the data is constructed, and the membership and prototype update equations are derived from necessary conditions for minimization of the criterion function.
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