| dc.contributor.author |
Holubinka, M. |
|
| dc.contributor.author |
Davis, A. |
|
| dc.contributor.author |
Zwiggelaar, Reyer |
|
| dc.contributor.author |
Marti, R. |
|
| dc.contributor.author |
Blot, L. |
|
| dc.date.accessioned |
2008-03-04T16:14:36Z |
|
| dc.date.available |
2008-03-04T16:14:36Z |
|
| dc.date.issued |
2002 |
|
| dc.identifier.citation |
Holubinka , M , Davis , A , Zwiggelaar , R , Marti , R & Blot , L 2002 , ' Automated quality assurance applied to mammographic imaging ' EURASIP Journal of Applied Signal Processing , vol 7 , pp. 736-745 . |
en |
| dc.identifier.issn |
1687-6180 |
|
| dc.identifier.other |
PURE: 75958 |
|
| dc.identifier.other |
dspace: 2160/527 |
|
| dc.identifier.uri |
http://hdl.handle.net/2160/527 |
|
| dc.identifier.uri |
http://www.hindawi.com/GetArticle.aspx?doi=10.1155/S1110865702203029 |
en |
| dc.description |
L. Blot, A. Davis, M. Holubinka, R. Marti and R. Zwiggelaar, 'Automated quality assurance applied to mammographic imaging', EURASIP Journal of Applied Signal Processing 2002 (7), 736-745 (2002) |
en |
| dc.description.abstract |
Quality control in mammography is based upon subjective interpretation of the image quality of a test phantom. In order to suppress subjectivity due to the human observer, automated computer analysis of the Leeds TOR(MAM) test phantom is investigated. Texture analysis via grey-level co-occurrence matrices is used to detect structures in the test object. Scoring of the substructures in the phantom is based on grey-level differences between regions and information from grey-level co-occurrence matrices. The results from scoring groups of particles within the phantom are presented. |
en |
| dc.format.extent |
10 |
en |
| dc.language.iso |
eng |
|
| dc.relation.ispartof |
EURASIP Journal of Applied Signal Processing |
en |
| dc.title |
Automated quality assurance applied to mammographic imaging |
en |
| dc.type |
Text |
en |
| dc.type.publicationtype |
Article (Journal) |
en |
| dc.identifier.doi |
http://dx.doi.org/10.1155/S1110865702203029 |
|
| dc.contributor.institution |
Department of Computer Science |
en |
| dc.contributor.institution |
Vision, Graphics and Visualisation Group |
en |
| dc.description.status |
Peer reviewed |
en |