Linked Life Data

18076823

Source:http://linkedlifedata.com/resource/pubmed/id/18076823

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2007-12-13
pubmed:abstractText
A 'virtual histology' can be thought of as the 'staining' of a digital ultrasound image via image processing techniques in order to enhance the visualisation of differences in the echotexture of different types of tissues. Several candidate image-processing algorithms for virtual histology using ultrasound images of the bovine ovary were studied. The candidate algorithms were evaluated qualitatively for the ability to enhance the visual differences in intra-ovarian structures and quantitatively, using standard texture description features, for the ability to increase statistical differences in the echotexture of different ovarian tissues. Certain algorithms were found to create textures that were representative of ovarian micro-anatomical structures that one would observe in actual histology. Quantitative analysis using standard texture description features showed that our algorithms increased the statistical differences in the echotexture of stroma regions and corpus luteum regions. This work represents a first step toward both a general algorithm for the virtual histology of ultrasound images and understanding dynamic changes in form and function of the ovary at the microscopic level in a safe, repeatable and non-invasive way.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1031-3613
pubmed:author
pubmed:issnType
Print
pubmed:volume
19
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
910-24
pubmed:dateRevised
2010-9-24
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Enhancing ultrasound texture differences for developing an in vivo 'virtual histology' approach to bovine ovarian imaging.
pubmed:affiliation
Department of Computer Science, The University of Saskatchewan, Saskatoon, Saskatchewan, Canada. eramian@cs.usask.ca
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't