Efficient inhomogeneity compensation using fuzzy c-means clustering models

Computer Methods and Programs in Biomedicine

Volumn 108, Issue 1, 2012, Pages 80-89

  Szilágyi, László ^a,b   Szilágyi, Sándor M ^a,b   Benyó, Balázs ^b  

^a SAPIENTIA HUNGARIAN UNIVERSITY OF TRANSYLVANIA   (Romania)

^b BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

Author keywords

C Means clustering; Histogram; Image segmentation; Intensity inhomogeneity; Magnetic resonance imaging

Indexed keywords

C-MEANS CLUSTERING; COMPENSATION TECHNIQUES; COMPUTATIONAL LOADS; FUZZY C MEANS CLUSTERING; FUZZY C-MEANS ALGORITHMS; GRAY INTENSITY; HIGH AMPLITUDES; HISTOGRAM; INHOMOGENEITIES; INTENSITY INHOMOGENEITY; MR IMAGES; NONUNIFORMITY; REGISTRATION METHODS; SEGMENTATION ACCURACY;

CLUSTERING ALGORITHMS; COPYING; FUZZY CLUSTERING; MAGNETIC RESONANCE IMAGING;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; FUZZY SYSTEM; IMAGE ANALYSIS; IMAGE INTENSIFIER; IMAGING AND DISPLAY; INTENSITY NON UNIFORMITY; NUCLEAR MAGNETIC RESONANCE IMAGING;

BRAIN; CLUSTER ANALYSIS; FUZZY LOGIC; HUMANS; MODELS, THEORETICAL;

EID: 84865730635     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2012.01.005     Document Type: Article

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