Automated Quality Assurance Applied to Mammographic Imaging
| Contribuinte(s) |
Vision, Graphics and Visualisation Group Department of Computer Science |
|---|---|
| Data(s) |
04/03/2008
04/03/2008
24/07/2002
|
| Resumo |
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) 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. Peer reviewed |
| Formato |
10 |
| Identificador |
Blot , L , Davis , A , Holubinka , M , Mart? , R & Zwiggelaar , R 2002 , ' Automated Quality Assurance Applied to Mammographic Imaging ' EURASIP Journal of Applied Signal Processing , vol 7 , pp. 736-745 . DOI: 10.1155/S1110865702203029 1687-6180 PURE: 75958 PURE UUID: 5ee5a1f0-2204-4199-8e2f-8dcd8789b964 dspace: 2160/527 |
| Relação |
EURASIP Journal of Applied Signal Processing |
| Idioma(s) |
eng |
| Direitos | |
| Tipo |
/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article |
