A neural network-based diagnostic method for solitary pulmonary nodules

Neurocomputing

Volumn 72, Issue 1-3, 2008, Pages 612-624

  Yeh, Chinson ^a   Lin, Chen Liang ^a   Wu, Ming Ting ^b,c   Yen, Chen Wen ^a   Wang, Jen Feng ^a  

^a NATIONAL SUN YAT SEN UNIVERSITY   (Taiwan)

^b KAOHSIUNG VETERANS GENERAL HOSPITAL   (Taiwan)

^c NATIONAL YANG MING UNIVERSITY   (Taiwan)

Author keywords

Computer aided diagnosis; Contrast enhancement; Lung cancer; Neural network; Solitary pulmonary nodule

Indexed keywords

BIOLOGICAL ORGANS; COMPUTER NETWORKS; COMPUTERIZED TOMOGRAPHY; DATA PROCESSING; ELECTRIC INSTRUMENT TRANSFORMERS; IMAGE CLASSIFICATION; NEURAL NETWORKS; POSITRON EMISSION TOMOGRAPHY;

CONTRAST ENHANCEMENT; CONTRAST ENHANCEMENTS; CT METHODS; CT SCANS; DIAGNOSTIC METHODS; DISTINCTIVE FEATURES; HIGH RESOLUTIONS; LUNG CANCER; LUNG NODULES; MORPHOMETRIC CHARACTERISTICS; MORPHOMETRY; PULMONARY NODULES; RADIATION EXPOSURES; SEMI AUTOMATICS; SOLITARY PULMONARY NODULE; TIME POINTS;

COMPUTER AIDED DIAGNOSIS;

CONTRAST MEDIUM;

ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; CLINICAL EFFECTIVENESS; COMPUTER ASSISTED DIAGNOSIS; CONTRAST ENHANCEMENT; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; FEMALE; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; IMAGE QUALITY; INTERMETHOD COMPARISON; LUNG CANCER; LUNG NODULE; LUNG PERFUSION; MAJOR CLINICAL STUDY; MALE; MULTIDETECTOR COMPUTED TOMOGRAPHY; PRIORITY JOURNAL; RADIATION DOSE; RADIATION EXPOSURE; RELIABILITY; TUMOR CLASSIFICATION;

EID: 55949101742     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.11.009     Document Type: Article

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