Effect of segmentation algorithms on the performance of computerized detection of lung nodules in CT

Medical Physics

Volumn 41, Issue 9, 2014, Pages

  Guo, Wei ^a   Li, Qiang ^b,c  

^a SHENYANG AEROSPACE UNIVERSITY   (China)

^b SHANGHAI ADVANCED RESEARCH INSTITUTE   (China)

^c DUKE UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

computer aided diagnosis; detection; lung nodule; segmentation

Indexed keywords

BIOLOGICAL ORGANS; CHEMICAL DETECTION; COMPUTER AIDED DIAGNOSIS; COMPUTERIZED TOMOGRAPHY; DATABASE SYSTEMS; ERROR DETECTION; GAUSSIAN DISTRIBUTION; OBJECT RECOGNITION;

COMPUTER-AIDED DETECTION; DETECTION OF LUNG NODULES; GAUSSIAN MIXTURE MODEL; LUNG NODULE; LUNG NODULE DETECTION; LUNG NODULE SEGMENTATION; MEAN ABSOLUTE DISTANCE; SEGMENTATION ALGORITHMS;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; CHAN AND VESE MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; FIXED THRESHOLDING; FUZZY SYSTEM; IMAGE PROCESSING; IMAGE SEGMENTATION; KERNEL METHOD; LOCAL BINARY FITTING; LUNG NODULE; OTSU THRESHOLDING; RADIOLOGICAL PARAMETERS; STANDARD; EVALUATION STUDY; FACTUAL DATABASE; FUZZY LOGIC; HUMAN; LABORATORY DIAGNOSIS; NORMAL DISTRIBUTION; PROCEDURES; RADIOGRAPHY; SENSITIVITY AND SPECIFICITY; SOLITARY PULMONARY NODULE; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; DATABASES, FACTUAL; FALSE POSITIVE REACTIONS; FUZZY LOGIC; HUMANS; IMAGING, THREE-DIMENSIONAL; LIKELIHOOD FUNCTIONS; NORMAL DISTRIBUTION; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; SENSITIVITY AND SPECIFICITY; SOLITARY PULMONARY NODULE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84921803860     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.4892056     Document Type: Article

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