Source:http://linkedlifedata.com/resource/pubmed/id/11976846
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
5
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| pubmed:dateCreated |
2002-4-26
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| pubmed:abstractText |
The aim of this study was to evaluate a computer-aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Eighty-eight consecutive spiral-CT examinations were reported by two radiologists in consensus. All examinations were reviewed using a CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm is designed to detect nodules with diameters of at least 5 mm. A total of 153 nodules were detected with at least one modality (radiologists in consensus, CAD, 85 nodules with diameter < 5 mm, 68 with diameter > or = 5 mm). The results of automatic nodule detection were compared to nodules detected with any modality as gold standard. Computer-aided diagnosis correctly identified 26 of 59 (38%) nodules with diameters > or = 5 mm detected by visual assessment by the radiologists; of these, CAD detected 44% (24 of 54) nodules without pleural contact. In addition, 12 nodules > or = 5 mm were detected which were not mentioned in the radiologist's report but represented real nodules. Sensitivity for detection of nodules > or = 5 mm was 85% (58 of 68) for radiologists and 38% (26 of 68) for CAD. There were 5.8+/-3.6 false-positive results of CAD per CT study. Computer-aided diagnosis improves detection of pulmonary nodules at spiral CT and is a valuable second opinion in a clinical setting for lung cancer screening despite of its still limited sensitivity.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
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| pubmed:month |
May
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| pubmed:issn |
0938-7994
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
12
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
1052-7
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| pubmed:dateRevised |
2004-11-17
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| pubmed:meshHeading |
pubmed-meshheading:11976846-Adult,
pubmed-meshheading:11976846-Aged,
pubmed-meshheading:11976846-Algorithms,
pubmed-meshheading:11976846-Diagnosis, Computer-Assisted,
pubmed-meshheading:11976846-False Positive Reactions,
pubmed-meshheading:11976846-Female,
pubmed-meshheading:11976846-Humans,
pubmed-meshheading:11976846-Lung Diseases,
pubmed-meshheading:11976846-Lung Neoplasms,
pubmed-meshheading:11976846-Male,
pubmed-meshheading:11976846-Middle Aged,
pubmed-meshheading:11976846-Sensitivity and Specificity,
pubmed-meshheading:11976846-Tomography, X-Ray Computed
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| pubmed:year |
2002
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| pubmed:articleTitle |
Automatic detection of pulmonary nodules at spiral CT: clinical application of a computer-aided diagnosis system.
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| pubmed:affiliation |
Department of Clinical Radiology, University of Muenster, 48129 Muenster, Germany. dag.wormanns@uni-muenster.de
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| pubmed:publicationType |
Journal Article
|