A wavelet-based optimal texture feature set for classification of brain tumours

Journal of Medical Engineering and Technology

Volumn 32, Issue 3, 2008, Pages 198-205

  Sasikala, M ^a   Kumaravel, N ^b  

^a ANNA UNIVERSITY   (India)

^b ANNA UNIVERSITY   (India)

Author keywords

Artificial neural network; Genetic algorithm; Spatial grey level dependence method; Texture features; Wavelet transform

Indexed keywords

BRAIN; FEATURE EXTRACTION; GENETIC ALGORITHMS; IMAGE ANALYSIS; NEURAL NETWORKS; TUMORS; WAVELET TRANSFORMS;

BRAIN IMAGES; SPATIAL GREY LEVEL DEPENDENCE METHODS; TEXTURE FEATURES;

IMAGE CLASSIFICATION;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BRAIN CANCER; BRAIN REGION; BRAIN TUMOR; CANCER CLASSIFICATION; COMPARATIVE STUDY; DIAGNOSTIC ACCURACY; ENERGY; GENETIC ANALYSIS; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PRINCIPAL COMPONENT ANALYSIS; RADIOLOGICAL PARAMETERS; VARIANCE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN NEOPLASMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 42449158125     PISSN: 03091902     EISSN: 1464522X     Source Type: Journal    
DOI: 10.1080/03091900701455524     Document Type: Article

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