Linked Life Data

3626993

Source:http://linkedlifedata.com/resource/pubmed/id/3626993

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1987-10-7
pubmed:abstractText
We have investigated the application of computer-based methods to the detection of microcalcifications in digital mammograms. The computer detection system is based on a difference-image technique in which a signal-suppressed image is subtracted from a signal-enhanced image to remove the structured background in a mammogram. Signal-extraction techniques adapted to the known physical characteristics of microcalcifications are then used to isolate microcalcifications from the remaining noise background. We employ Monte Carlo methods to generate simulated clusters of microcalcifications that are superimposed on normal mammographic backgrounds. This allows quantitative evaluation of detection accuracy of the computer method and the dependence of this accuracy on the physical characteristics of the microcalcifications. Our present computer method can achieve a true-positive cluster detection rate of approximately 80% at a false-positive detection rate of one cluster per image. The potential application of such a computer-aided system to mammographic interpretation is demonstrated by its ability to detect microcalcifications in clinical mammograms.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0094-2405
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
538-48
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:articleTitle
Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't