Brain tissue classification based on DTI using an improved Fuzzy C-means algorithm with spatial constraints

Magnetic Resonance Imaging

Volumn 31, Issue 9, 2013, Pages 1623-1630

  Wen, Ying ^a   He, Lianghua ^b   von Deneen, Karen M ^c   Lu, Yue ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

^b Department of Computer Science and Technology   (China)

^c XIDIAN UNIVERSITY   (China)

Author keywords

Diffusion tensor imaging; Fuzzy c means with spatial constraints; Image segmentation; Parametric map

Indexed keywords

ARTICLE; BRAIN TISSUE; CLASSIFICATION ALGORITHM; CLUSTER ANALYSIS; DIFFUSION TENSOR IMAGING; FUZZY SYSTEM; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE QUALITY; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SIGNAL NOISE RATIO; TISSUE CHARACTERIZATION; VALIDATION PROCESS; ALGORITHM; ANISOTROPY; ARTIFACT; AUTOMATED PATTERN RECOGNITION; AUTOMATION; BRAIN; FUZZY LOGIC; HUMAN; NORMAL DISTRIBUTION; PATHOLOGY; TIME;

ALGORITHMS; ANISOTROPY; ARTIFACTS; AUTOMATION; BRAIN; CLUSTER ANALYSIS; DIFFUSION TENSOR IMAGING; FUZZY LOGIC; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; NORMAL DISTRIBUTION; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; TIME FACTORS;

EID: 84885053531     PISSN: 0730725X     EISSN: 18735894     Source Type: Journal    
DOI: 10.1016/j.mri.2013.05.007     Document Type: Article

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