An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation

An adaptive spatial fuzzy c-means clustering algorithm is presented in this paper for the segmentation of three-dimensional (3-D) magnetic resonance (MR) images. The input images may be corrupted by noise and intensity nonuniformity (INU) artifact. The proposed algorithm takes into account the spati...

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Veröffentlicht in:	IEEE transactions on medical imaging 2003-09, Vol.22 (9), p.1063-1075
Hauptverfasser:	Liew, A.W.C., Hong Yan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Anatomy, Cross-Sectional - methods Bias Biological and medical sciences Brain - anatomy & histology Cluster Analysis Clustering algorithms Computer Simulation Continuity Feedback Fuzzy Fuzzy Logic Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image segmentation Imaging, Three-Dimensional - methods Information technology Magnetic noise Magnetic resonance Magnetic resonance imaging Magnetic Resonance Imaging - methods Mathematical models Medical sciences Noise reduction Nonuniform electric fields Pattern Recognition, Automated Pixel Reproducibility of Results Segmentation Sensitivity and Specificity Spline Studies
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