Linked Life Data

16639398

Source:http://linkedlifedata.com/resource/pubmed/id/16639398

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2006-4-26
pubmed:abstractText
We have developed an automated computerized method for the detection of lung nodules in three-dimensional (3D) computed tomography (CT) images obtained by helical CT. In this scheme, a lung segmentation technique for the determination of the nodule search area is performed based on a gray-level thresholding technique. To enhance lung nodules, we employed the 3D cross-correlation method by using a 3D Gaussian template with zero-surrounding as a model of lung nodule. False positives are then eliminated by using a rule-base with 53 features. For further reduction of false positives, we performed linear discriminant analysis using these 53 features. The average number of false positives was 6.7 per case at a percent sensitivity of 85.0%. This computerized scheme will be useful to radiologists by providing a "second opinion" in case of possible early lung cancer.
pubmed:language
jpn
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0369-4305
pubmed:author
pubmed:issnType
Print
pubmed:day
20
pubmed:volume
62
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
555-64
pubmed:dateRevised
2011-7-28
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
[Development of computer-aided diagnostic system for detection of lung nodules in three-dimensional computed tomography images].
pubmed:affiliation
Hiroshima International University, Department of Clinical Radiology.
pubmed:publicationType
Journal Article, English Abstract