Recognizing common CT imaging signs of lung diseases through a new feature selection method based on fisher criterion and genetic optimization

IEEE Journal of Biomedical and Health Informatics

Volumn 19, Issue 2, 2015, Pages 635-647

  Liu, Xiabi ^a   Ma, Ling ^a   Song, Li ^a,b   Zhao, Yanfeng ^c   Zhao, Xinming ^c   Zhou, Chunwu ^c  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b Qihoo 360 Technology Co Ltd   (China)

^c CANCER HOSPITAL   (China)

Author keywords

Common CT imaging signs of lung diseases (CISLs); feature selection; lung CT images; lung lesion classification; medical image classification

Indexed keywords

ADAPTIVE BOOSTING; BIOLOGICAL ORGANS; COMPUTERIZED TOMOGRAPHY; DIAGNOSIS; GRAPHIC METHODS; IMAGE CLASSIFICATION; MEDICAL IMAGING; NEAREST NEIGHBOR SEARCH; STATISTICAL METHODS; SUPPORT VECTOR MACHINES; WAVELET TRANSFORMS;

CLASSIFICATION ACCURACY; CT IMAGING; EFFECTIVENESS AND EFFICIENCIES; FEATURE SELECTION METHODS; GENETIC OPTIMIZATION ALGORITHM; HISTOGRAM OF ORIENTED GRADIENTS; LUNG CT; LUNG LESIONS;

FEATURE EXTRACTION;

ALGORITHM; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; FACTUAL DATABASE; HUMAN; LUNG; LUNG DISEASE; PATHOLOGY; PROCEDURES; RADIOGRAPHY;

ALGORITHMS; BAYES THEOREM; DATABASES, FACTUAL; HUMANS; LUNG; LUNG DISEASES; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84924725055     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2014.2327811     Document Type: Article

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