Linked Life Data

16967807

Source:http://linkedlifedata.com/resource/pubmed/id/16967807

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
9
pubmed:dateCreated
2006-9-13
pubmed:abstractText
Screening programs using retinal photography for the detection of diabetic eye disease are being introduced in the UK and elsewhere. Automatic grading of the images is being considered by health boards so that the human grading task is reduced. Microaneurysms (MAs) are the earliest sign of this disease and so are very important for classifying whether images show signs of retinopathy. This paper describes automatic methods for MA detection and shows how image contrast normalization can improve the ability to distinguish between MAs and other dots that occur on the retina. Various methods for contrast normalization are compared. Best results were obtained with a method that uses the watershed transform to derive a region that contains no vessels or other lesions. Dots within vessels are handled successfully using a local vessel detection technique. Results are presented for detection of individual MAs and for detection of images containing MAs. Images containing MAs are detected with sensitivity 85.4% and specificity 83.1%.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0278-0062
pubmed:author
pubmed:issnType
Print
pubmed:volume
25
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1223-32
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Automated microaneurysm detection using local contrast normalization and local vessel detection.
pubmed:affiliation
Biomedical Physics, University of Aberdeen, Aberdeen, AB25 2ZD, UK. a.fleming@biomed.abdn.ac.uk
pubmed:publicationType
Journal Article