Linked Life Data

9667049

Source:http://linkedlifedata.com/resource/pubmed/id/9667049

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
1998-9-17
pubmed:abstractText
Parathyroid subtraction imaging using the radioisotopes thallium-201 and technetium-99m was first described in 1983. Since then it has become a routine method for the pre-operative localization of parathyroid tumours. Despite its widespread use, the interpretation of the subtraction images remains very subjective. This paper describes and evaluates an automatic objective method for the analysis of parathyroid scans. The method is based on the calculation of a likelihood ratio (the probability of obtaining a count in a given pixel if a tumour is present divided by the probability of obtaining that same count if a tumour is not present). The likelihood ratio is calculated for each pixel in a subtraction image. The calculated value is compared with a threshold. Pixels with likelihood ratios greater than the threshold are classified as belonging to tumour sites. Pixels with likelihood ratios less than, or equal to, the threshold are classified as belonging to 'no tumour' sites. The probability density functions required were obtained from computer simulated images. The likelihood ratio technique has a similar sensitivity and specificity to that of experienced human observers analysing computer simulated images. Furthermore, it is a completely automatic method which can provide the basis of a decision support system.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0307-7640
pubmed:author
pubmed:issnType
Print
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
159-71
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:articleTitle
Modelling dual isotope parathyroid scans: objective decision making for tumour detection.
pubmed:affiliation
Department of Medical Physics and Clinical Engineering, Royal Hallamshire Hospital, Sheffield, UK.
pubmed:publicationType
Journal Article