Differentiation between nodules and end-on vessels using a convolution neural network architecture

Journal of Digital Imaging

Volumn 8, Issue 3, 1995, Pages 132-141

  Lin, Jyh Shyan ^a   Hasegawa, Akira ^a   Freedman, Matthew T ^a   Mun, Seong K ^a  

^a GEORGETOWN UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

and receiver operating characteristics (ROC); computer aided diagnosis (CADx); Convolution neural network (CNN); feature map

Indexed keywords

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BREAST DISEASE; CALCINOSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; FEMALE; HUMAN; IMAGE QUALITY; LABORATORY DIAGNOSIS; LUNG; LUNG DISEASE; MAMMOGRAPHY; RADIOGRAPHY; RADIOLOGY; ROC CURVE; SENSITIVITY AND SPECIFICITY; THORAX RADIOGRAPHY; VASCULARIZATION;

ALGORITHMS; ARTIFACTS; BREAST DISEASES; CALCINOSIS; COMPUTER SIMULATION; DIAGNOSIS, COMPUTER-ASSISTED; FALSE POSITIVE REACTIONS; FEMALE; HUMANS; LUNG; LUNG DISEASES; MAMMOGRAPHY; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHY, THORACIC; RADIOLOGY; ROC CURVE; SENSITIVITY AND SPECIFICITY;

EID: 0029347997     PISSN: 08971889     EISSN: 1618727X     Source Type: Journal    
DOI: 10.1007/BF03168087     Document Type: Article

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