Impact of Textured Background on Scoring of Simulated CDMAM Phantom
CDMAM phantom scoring is widely used to assess the detectability performance of mammography systems. We propose to study the impact of structured background on this performance assessment, using simulated CDMAM phantom images with flat and textured backgrounds. Three dose levels have been investigated, ranging from -50% to +50% around the reference dose computed by the acquisition system. For textured backgrounds, the simulated projected breast corresponds to a 50mm thick, 60% glandular breast, with a texture generated by a power-law filtered noise model. Images have been scored by four image quality experts. For the smaller insert sizes, Image Quality Factor (IQF) scores obtained in textured backgrounds are lower than and well correlated with those obtained in flat backgrounds. IQF values increased with dose. For the larger insert sizes, detectability performance in textured background is even more degraded and is not as dose dependent as it is in flat backgrounds.
KeywordsDetection Performance Insert Size Digital Mammography Structure Background Digital Mammogram
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- 5.Bijkerk, K., Thijssen, M., Arnoldussen, Th.: Manual CDMAM-phantom type 3.4. University Medical Centre, Nijmegen, The Netherlands (2000)Google Scholar
- 6.Grosjean, B., Muller, S., Souchay, H., Rico, R., Bouchevreau, X.: Automated scoring for CDMAM phantom from simulated images. In: Proceedings of IWDM 2004 (2004)Google Scholar
- 7.Burgess, A.E.: Bach, breasts, and power-law processes. In: Proceedings of SPIE, vol. 4324, pp. 103–113 (2001)Google Scholar
- 9.Grosjean, B., Muller, S., Souchay, H.: Lesion detection using an a-contrario detector in simulated digital mammograms. In: Proceedings of SPIE (to be published, 2006)Google Scholar
- 10.Shramchenko, N., Blin, P., Mathey, C., Klausz, R.: Optimized exposure control in digital mammography. In: Proceedings of SPIE, vol. 5368, pp. 445–456 (2004)Google Scholar
- 11.Burgess, A.E., Jacobson, F.L., Judy, P.F.: Lesion detection in digital mammograms. In: Proceedings of SPIE, vol. 4320, pp. 555–560 (2001)Google Scholar
- 12.Burgess, A.E.: Evaluation of detection model performance in power-law noise. In: Proceedings of SPIE, vol. 4324, pp. 123–132 (2001)Google Scholar
- 15.Van Metter, R., Health, M.D., Fletcher-Health, L.M.: Applying the European protocol for the quality control of the physical and technical aspect of mammography screening to digital systems. In: Proceeding of SPIE (to be published, 2006)Google Scholar
- 16.Young, K.C., Cook, J.J., Oduko, J.M., Bosmans, H.T.: Comparison of software and human observers in reading images of the CDMAM test object to assess digital mammography systems. In: Proceeding of SPIE (to be published, 2006)Google Scholar
- 19.Chawla, A.S., Saunders, R.S., Samei, E.: Effect of dose reduction on the detection of mammographic lesions based on mathematical observer models. In: Proceedings of SPIE (to be published, 2006)Google Scholar