Classification of pulmonary nodules by using hybrid features

Computational and Mathematical Methods in Medicine

Volumn 2013, Issue , 2013, Pages

  Tartar, Ahmet ^a   Kilic, Niyazi ^a   Akan, Aydin ^a  

^a ISTANBUL UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ACCURACY; CLASSIFICATION APPROACH; DETECTION PERFORMANCE; HYBRID FEATURES; LUNG CANCER; PULMONARY NODULES;

COMPUTERIZED TOMOGRAPHY;

ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; EARLY DIAGNOSIS; FEMALE; HUMAN; IMAGE PROCESSING; LEARNING ALGORITHM; LUNG NODULE; LUNG PARENCHYMA; MAJOR CLINICAL STUDY; MALE; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; RADIOLOGIST; RANDOM FOREST; SENSITIVITY AND SPECIFICITY; ALGORITHM; BIOLOGY; CLASSIFICATION; COMPARATIVE STUDY; EVALUATION STUDY; LUNG NEOPLASMS; MIDDLE AGED; MULTIPLE PULMONARY NODULES; PROCEDURES; RADIOGRAPHY; STATISTICS AND NUMERICAL DATA; LUNG TUMOR; METHODOLOGY; STATISTICS;

ADULT; AGED; ALGORITHMS; COMPUTATIONAL BIOLOGY; FEMALE; HUMANS; LUNG NEOPLASMS; MALE; MIDDLE AGED; MULTIPLE PULMONARY NODULES; NEURAL NETWORKS (COMPUTER); PRINCIPAL COMPONENT ANALYSIS; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; SOLITARY PULMONARY NODULE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84880180582     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2013/148363     Document Type: Article

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