A revisit on correlation between Tabár and Birads based risk assessment schemes with full field digital mammography

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8539 LNCS, Issue , 2014, Pages 327-333

  He, Wenda ^a   Kibiro, Minnie ^b   Juette, Arne ^b   Denton, Erika R E ^b   Zwiggelaar, Reyer ^a  

^a ABERYSTWYTH UNIVERSITY   (United Kingdom)

^b NORFOLK AND NORWICH UNIVERSITY HOSPITAL   (United Kingdom)

Author keywords

Birads; digital mammography; risk assessment; Tab r

Indexed keywords

COMPUTER AIDED DIAGNOSIS; MAMMOGRAPHY; MIXTURES; RISK ASSESSMENT;

ASSESSMENT SCHEME; BI-RADS; CORRELATION COEFFICIENT; DIGITAL MAMMOGRAPHY; DISEASE PREVENTION; FULL FIELD DIGITAL MAMMOGRAPHY; READER VARIABILITY; STRONG CORRELATION;

MEDICAL IMAGING;

EID: 84904009011     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-07887-8_46     Document Type: Conference Paper

References (14)

1. Cancer statistics registrations, England, 2011. MB1(42) (June 2013)
2. Mukhtar, T.K., Yeates, D.R., Goldacre, M.J.: Breast cancer mortality trends in England and the assessment of the effectiveness of mammography screening: population-based study. Journal of the Royal Society of Medicine 6, 234-242 (2013)
3. DeSantis, C., Ma, J., Bryan, L., Jemal, A.: Breast cancer statistics. CA: A Cancer Journal for Clinicians (2013)
4. Eccles, S.A., et al.: Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer. Breast Cancer Research 15(R92) (2013)
5. Colin, C., Prince, V., Valette, P.J.: Can mammographic assessments lead to consider density as a risk factor for breast cancer? European Journal of Radiology 82(3), 404-411 (2013)
6. Tabár, L., Tot, T., Dean, P.B.: Breast Cancer: The Art and Science of Early Detection With Mamography: Perception, Interpretation, Histopatholigic Correlation, 1st edn. Georg Thieme Verlag (December 2004)
7. American College of Radiology. Breast Imaging Reporting and Data System BIRADS, 4th edn. American College of Radiology, Reston (2004)
8. Tzias, D., George, S., Wilkinson, L., Mehta, R.: Quantification of breast cancer risk based on the UK five-point classification system. Breast Cancer Research 13:S4 (November 2011)
9. Gail, M.H., Brinton, L.A., Byar, D.P., Corle, D.K., Green, S.B., Schairer, C., Mulvihill, J.J.: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. Journal of the National Cancer Institute 81(24), 1879-1886 (1989)
10. Tyrer, J., Duffy, S.W., Cuzick, J.: A breast cancer prediction model incorporating familial and personal risk factors. Statistics in Medicine 23, 1111-1130 (2004)
11. Wolfe, J.N.: Breast patterns as an index of risk for developing breast cancer. American Journal of Roentgenology 126(6), 1130-1137 (1976)
12. Sickles, E.A.: Wolfe mammographic parenchymal patterns and breast cancer risk. American Journal of Roentgenology 188(2), 301-303 (2007)
13. Gram, I.T., Bremnes, Y., Ursin, G., Maskarinec, G., Bjurstam, N., Lund, E.: Percentage density, Wolfe's and Tabár's mammographic patterns: agreement and association with risk factors for breast cancer. Breast Cancer Research 7, 854-861 (2005)
14. Muhimmah, I., Oliver, A., Denton, E.R.E., Pont, J., Pérez, E., Zwiggelaar, R.: Comparison between Wolfe, Boyd, BI-RADS and Tabár based mammographic risk assessment. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds.) IWDM 2006. LNCS, vol. 4046, pp. 407-415. Springer, Heidelberg (2006) (Pubitemid 44113138)