Breast tumor detection in digital mammography based on extreme learning machine

Neurocomputing

Volumn 128, Issue , 2014, Pages 175-184

  Wang, Zhiqiong ^a,b   Yu, Ge ^b   Kang, Yan ^a   Zhao, Yingjie ^c   Qu, Qixun ^a  

^a NORTHEASTERN UNIVERSITY   (China)

^b NORTHEASTERN UNIVERSITY   (China)

^c Tumor Hospital of Liaoning Province   (China)

Author keywords

Breast tumor detection; Extreme learning machine; Feature extraction; Image segmentation; Mammography

Indexed keywords

BREAST TUMOR DETECTION; CLASSIFICATION ACCURACY; CONTRAST ENHANCEMENT; EXTREME LEARNING MACHINE; GENERALIZATION ABILITY; MORPHOLOGICAL FEATURES; MORPHOLOGICAL OPERATIONS; WAVELET MODULUS MAXIMA;

COMPUTER AIDED DIAGNOSIS; FEATURE EXTRACTION; IMAGE SEGMENTATION; KNOWLEDGE ACQUISITION; MAMMOGRAPHY; MATHEMATICAL MORPHOLOGY; NOISE ABATEMENT; SUPPORT VECTOR MACHINES;

TUMORS;

ADULT; AGED; ARTICLE; BREAST TUMOR; CLASSIFIER; CONTRAST ENHANCEMENT; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DIGITAL MAMMOGRAPHY; EXTREME LEARNING MACHINE; FEMALE; HUMAN; IMAGE ENHANCEMENT; IMAGE PROCESSING; INTERMETHOD COMPARISON; LEARNING ALGORITHM; MACHINE LEARNING; MAJOR CLINICAL STUDY; MORPHOLOGY; NOISE REDUCTION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; RECEIVER OPERATING CHARACTERISTIC; SUPPORT VECTOR MACHINE; TUMOR CLASSIFICATION; TUMOR DIAGNOSIS; TUMOR GROWTH; VALIDATION PROCESS; WAVELET ANALYSIS; WAVELET MODULUS MAXIMA TRANSFORM ALGORITHM;

EID: 84893703234     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.05.053     Document Type: Article

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