Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network

IEEE Transactions on Medical Imaging

Volumn 24, Issue 9, 2005, Pages 1138-1150

  Suzuki, Kenji ^a   Li, Feng ^a   Sone, Shusuke ^b   Doi, Kunio ^a  

^a UNIVERSITY OF CHICAGO   (United States)

^b Azumi General Hospital   (Japan)

Author keywords

Artificial neural network; Computer aided diagnosis (CAD); Likelihood of malignancy; Low dose CT; Lung nodule

Indexed keywords

BIOLOGICAL ORGANS; COMPUTER AIDED DIAGNOSIS; DATABASE SYSTEMS; DOSIMETRY; IMAGE PROCESSING; NEURAL NETWORKS; TUMORS;

LIKELIHOOD OF MALIGNANCY; LOW-DOSE CT; LUNG NODULE;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE QUALITY; LUNG COIN LESION; LUNG TUMOR; METHODOLOGY; RADIATION DOSE; RADIOGRAPHY; REPRODUCIBILITY; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; SPIRAL COMPUTER ASSISTED TOMOGRAPHY; THORAX RADIOGRAPHY; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COIN LESION, PULMONARY; HUMANS; LUNG NEOPLASMS; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; RADIATION DOSAGE; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, SPIRAL COMPUTED;

EID: 25144514408     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2005.852048     Document Type: Article

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