Automated quality assurance applied to mammographic imaging

被引：2

作者：

Blot, L ^{[1
]}

Davis, A

Holubinka, M

Marti, R

Zwiggelaar, R

机构：

[1] Univ E Anglia, Sch Informat Syst, Norwich NR4 7TJ, Norfolk, England

[2] Portsmouth Hosp NHS Trust, Portsmouth PO3 6AD, Hants, England

来源：

EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING | 2002年 / 2002卷 / 07期

关键词：

automatic quality control; mammographic images; grey-level co-occurrence matrices; image segmentation;

D O I：

10.1155/S1110865702203029

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：736 / 745

页数：10

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