Computerized analysis of tissue density effect on missed cancer detection in digital mammography.
This paper presents a study of the analysis of breast density in missed cancer cases and the effect of tissue density on cancer detection. A total of 100 missed cancer cases were collected. The breast density tissue was segmented with a statistical-based method. A set of tests was then applied to examine: (1) the differences in density between the mammograms at the detected stage and that at missed stage; (2) the density difference between the cancerous mammograms and their contra-lateral normal mammograms in the missed cancer cases; (3) the effect of breast density on CAD cancer detection. The results demonstrate that breast density is an important factor affecting not only radiologist's reading but also CAD performance. In order to improve early detection of breast cancer, a special effort should be directed to the high dense breast cases in CAD system design.
Li
Lihua
L
Department of Interdisciplinary Oncology, H. Lee Moffitt Cancer Center & Research Institute, University of South Florida, 12902 Magnolia Dr., Tampa, FL 33612, USA. lilh@moffitt.usf.edu
Wu
Zuobao
Z
Salem
Angela
A
Chen
Zhao
Z
Chen
Li
L
George
Florence
F
Kallergi
Maria
M
Berman
Claudia
C
D001943:Breast Neoplasms / Q000175:diagnosis*; D003238:Connective Tissue; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008327:Mammography / Q000379:methods*; D014481:United States