A new wavelet transform to sparsely represent cortical current densities for EEG/MEG inverse problems

Computer Methods and Programs in Biomedicine

Volumn 111, Issue 2, 2013, Pages 376-388

  Liao, Ke ^a   Zhu, Min ^a   Ding, Lei ^a,b  

^a University of Oklahoma   (United States)

^b UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

Compressed sensing; Compressibility; EEG MEG; Inverse problem; Sparseness; Wavelet transform

Indexed keywords

COHERENT MEASUREMENT; COMPRESSION METHODS; CORTICAL STRUCTURES; CORTICAL SURFACES; CURRENT DENSITY DISTRIBUTION; MEASUREMENT SYSTEM; SPARSENESS; TRANSFORM DOMAIN;

COMPRESSED SENSING; COMPRESSIBILITY; COMPUTER GRAPHICS; CURRENT DENSITY; INVERSE PROBLEMS; INVERSE TRANSFORMS; MONTE CARLO METHODS;

WAVELET TRANSFORMS;

ARTICLE; COMPRESSION; COMPUTER PROGRAM; ELECTROENCEPHALOGRAM; MAGNETOENCEPHALOGRAPHY; MONTE CARLO METHOD; NERVE CONDUCTION; SURFACE PROPERTY; WAVELET ANALYSIS;

COMPRESSED SENSING; COMPRESSIBILITY; EEG/MEG; INVERSE PROBLEM; SPARSENESS; WAVELET TRANSFORM;

ALGORITHMS; AREA UNDER CURVE; BRAIN MAPPING; CEREBRAL CORTEX; COMPUTER GRAPHICS; COMPUTER SIMULATION; DATA COMPRESSION; ELECTROENCEPHALOGRAPHY; EPILEPSY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LANGUAGE; MAGNETOENCEPHALOGRAPHY; MODELS, STATISTICAL; MONTE CARLO METHOD; SOFTWARE; WAVELET ANALYSIS;

EID: 84880039753     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2013.04.015     Document Type: Article

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