Probabilistic Identification and Estimation of Noise (PIESNO): A self-consistent approach and its applications in MRI

Journal of Magnetic Resonance

Volumn 199, Issue 1, 2009, Pages 94-103

  Koay, Cheng Guan ^a   Özarslan, Evren ^a   Pierpaoli, Carlo ^a  

^a EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT   (United States)

Author keywords

Gamma distribution; Graphical analysis of noise; MR noise; Noise clustering; Noise identification; Noise variance estimation; Rayleigh distribution

Indexed keywords

GAMMA DISTRIBUTION; GRAPHICAL ANALYSIS OF NOISE; MR NOISE; NOISE CLUSTERING; NOISE IDENTIFICATION; NOISE VARIANCE ESTIMATION; RAYLEIGH DISTRIBUTION;

DATA STRUCTURES; ESTIMATION; GAUSSIAN NOISE (ELECTRONIC); NOISE POLLUTION CONTROL; PIXELS; STATISTICS;

CLUSTER ANALYSIS;

ALGORITHM; ARTICLE; ARTIFACT; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFACTS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 67349192934     PISSN: 10907807     EISSN: 10960856     Source Type: Journal    
DOI: 10.1016/j.jmr.2009.03.005     Document Type: Article

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