The relationship between anatomic noise and volumetric breast density for digital mammography

Medical Physics

Volumn 39, Issue 8, 2012, Pages 4660-4668

  Mainprize, James G ^a   Tyson, Albert H ^a   Yaffe, Martin J ^b,c  

^a Canada   (Canada)

^b SUNNYBROOK RESEARCH INSTITUTE   (Canada)

^c Department of Medical Biophysics ^*  (Canada)

Author keywords

anatomic noise; breast density; digital mammography; image analysis

Indexed keywords

IMAGE ANALYSIS; INVERSE PROBLEMS; MAMMOGRAPHY; OPTICAL TRANSFER FUNCTION; QUANTUM NOISE; TEXTURES; X RAY SCREENS;

ANATOMIC NOISE; BREAST DENSITY; DIGITAL MAMMOGRAPHY; FIBROGLANDULAR TISSUE; PREDICTIVE INFORMATION; PROBABILISTIC MODELS; REGIONS OF INTEREST; VOLUMETRIC BREAST DENSITIES;

MEDICAL IMAGING;

EID: 84864662390     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.4736422     Document Type: Article

References (19)

1. A. E. Burgess, Statistically defined backgrounds: performance of a modified nonprewhitening observer model., J. Opt. Soc. Am. A 11, 1237-1242 (1994). 10.1364/JOSAA.11.001237
2. A. E. Burgess, On the detection of lesions in mammographic structure., Proc. SPIE 3663, 419-437 (1999). 10.1117/12.349655
3. E. Engstrom, I. Reiser, and R. Nishikawa, Comparison of power spectra for tomosynthesis projections and reconstructed images., Med. Phys. 36, 1753-1758 (2009). 10.1118/1.3116774
4. V. A. McCormack and I. dos Santos Silva, Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis., Cancer Epidemiol. Biomarkers Prev. 15, 1159-1169 (2006). 10.1158/1055-9965.EPI-06-0034
5. N. F. Boyd, G. A. Lockwood, J. W. Byng, D. L. Tritchler, and M. J. Yaffe, Mammographic densities and breast cancer risk., Cancer Epidemiol. Biomarkers Prev. 7, 1133-1144 (1998). (Pubitemid 29001671)
6. A. Saftlas, R. Hoover, L. A. Brinton, M. Szklo, D. Olson, M. Salane, and J. N. Wolfe, Mammographic densities and risk of breast cancer., Cancer 67, 2833-2838 (1991). 10.1002/1097-0142(19910601)67:113C2833::AID-CNCR28206711213E3. 0.CO;2-U
7. O. Alonzo-Proulx, N. Packard, J. M. Boone, A Al-Mayah, K. K. Brock, S. Z. Shen, and M. J. Yaffe, Validation of a method for measuring the volumetric breast density from digital mammograms., Phys. Med. Biol. 55, 3027-3044 (2010). 10.1088/0031-9155/55/11/003
8. M. Ge, G. Mawdsley, and M. Yaffe, Automatic identification of pectoralis muscle on digital cranio-caudal-view mammograms., Proc. SPIE 7963, 79631W-79631W-8 (2011). 10.1117/12.878785
9. G. E. Mawdsley, A. H. Tyson, C. L. Peressotti, R. a. Jong, and M. J. Yaffe, Accurate estimation of compressed breast thickness in mammography., Med. Phys. 36, 577-586 (2009). 10.1118/1.3065068
10. A. H. Tyson, G. E. Mawdsley, and M. J. Yaffe, Measurement of compressed breast thickness by optical stereoscopic photogrammetry., Med. Phys. 36, 569-576 (2009). 10.1118/1.3065066
11. O. Alonzo-Proulx, J. Mainprize, and N. Packard, Development of a peripheral thickness estimation method for volumetric breast density measurements in mammography using a 3D finite element breast model., Lect. Notes Comput. Sci. 6136, 467-473 (2010). 10.1007/978-3-642-13666-5
12. D. Rico, J. Yang, B. J. Augustine, G. E. Mawdsley, and M. J. Yaffe, Peripheral thickness correction for volumetric breast density estimation., in Proceedings of the 6th International Workshop on Digital Mammography (Bremen), edited by, H.-O. Peitgen, (Springer, Bremen, 2002), pp. 187-191.
13. J. W. Byng, J. G. Mainprize, and M. J. Yaffe, X-ray characterization of breast phantom materials., Phys. Med. Biol. 43, 1367-1377 (1998). 10.1088/0031-9155/43/5/026 (Pubitemid 28223579)
14. A. E. Burgess, F. L. Jacobson, and P. F. Judy, Human observer detection experiments with mammograms and power-law noise., Med. Phys. 28, 419-437 (2001). 10.1118/1.1355308 (Pubitemid 32323293)
15. M. J. Yaffe, J. M. Boone, N. Packard, O. Alonzo-Proulx, S.-Y. Huang, C. L. Peressotti, A. Al-Mayah, and K. Brock, The myth of the 50-50 breast., Med. Phys. 36, 5437-5443 (2009). 10.1118/1.3250863
16. J. G. Mainprize and M. J. Yaffe, Cascaded analysis of signal and noise propagation through a heterogeneous breast model., Med. Phys. 37, 5243-5250 (2010). 10.1118/1.3483095
17. K. G. Metheany, C. K. Abbey, N. Packard, and J. M. Boone, Characterizing anatomical variability in breast CT images., Med. Phys. 35, 4685-4694 (2008). 10.1118/1.2977772
18. J. N. Wolfe, Risk for breast cancer development determined by mammographic parenchymal pattern., Cancer 37, 2486-2492 (1976). 10.1002/1097-0142(197605)37:53C2486::AID-CNCR28203705423E3.0.CO;2-8
19. One slight variation from the algorithm presented in Ref. is the manner in which the search for the margin region was performed. In the original approach, each radial line was subdivided into ten intervals on which the slope of the relative transmission was computed. The interval with the minimum slope was identified to determine the baseline transmission believed to correspond to the breast region that had been compressed to constant thickness. Using this transmission value, the point at which the relative transmission departed from the baseline transmission was identified as the rough boundary of the uniform thickness region. In this work, however, a coarser step size of four intervals was found to be sufficient to locating the minimum slope.