Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy c-means approach to tissue classification in multimodal medical imaging
Information Sciences—Informatics and Computer Science: An International Journal
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
IEEE Transactions on Information Technology in Biomedicine
Knowledge and intelligent computing system in medicine
Computers in Biology and Medicine
An efficient hybrid data clustering method based on K-harmonic means and Particle Swarm Optimization
Expert Systems with Applications: An International Journal
A novel hybrid K-harmonic means and gravitational search algorithm approach for clustering
Expert Systems with Applications: An International Journal
Black hole: A new heuristic optimization approach for data clustering
Information Sciences: an International Journal
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Hyperdensity in head CT images has been shown to be a specific feature for diagnosing tuberculous meningitis (TBM) in children. We describe the extraction of hyperdense regions using fuzzy c-means clustering and fuzzy maximum likelihood estimation, thus providing a tool for the enhancement of an often subtle radiological feature. We calculate an asymmetry measure and confirm that normal and TBM images have different patterns of hyperdensity. Our results may be used in computer-assisted diagnosis of TBM.