On the difficulty of detecting tumors in mammograms

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

Volumn 2082, Issue , 2001, Pages 1-11

  Burgess, Arthur E ^a   Jacobson, Francine L ^a   Judy, Philip F ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERIZED TOMOGRAPHY; MAMMOGRAPHY; TUMORS; WHITE NOISE;

CONTRAST THRESHOLD; CORRECTION FACTORS; DETECTABILITY; FILTERED NOISE; HUMAN OBSERVERS; HUMAN PERFORMANCE; MAMMOGRAPHIC STRUCTURE; OBSERVER MODELS;

MEDICAL IMAGING;

EID: 84937421775     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45729-1_1     Document Type: Conference Paper

References (28)

1. Revesz, G., Kundel, H.L., Graber, M.A.: The influence of structured noise on detection of radiologic abnormalities. Invest. Radiol. 9 (1974) 479–486
2. Kundel, H.L., Nodine, C.F., Thickman, D. Carmody, D., et al.: Nodule detection with and without a chest image. Invest. Radiol. 20 (1985) 94-99
3. Judy, P.F., Swensson, R.G., Nawfel, R.D., Chan K.H.: Contast detail curves for liver CT Med. Phys. 19 (1992) 1167–1174
4. Bochud, F.O., Verdun, F.R., Valley, J.F., Hessler C., et al.: The importance of anatomical noise in mammography Proc. SPIE 3036 (1997) 74–80
5. Bochud, F.O., Abbey, C.K., Eckstein, M.P.: Further inverstigation of the effect of phase spectrum on visual detection in structured backgrounds Proc. SPIE 3663 (1999) 273–281
6. Bochud, F.O., Valley, J.F., Verdun F.R., Hessler C., et al.: Estimate of the noisy component of anatomical backgrounds Med. Phys. 26 (1999) 1365–1370
7. Zheng, B., Chang, Y.-H., Gur, D.: Adaptive computer-aided diagnosis scheme of digitized mammograms. Acad. Radiol. 3 (1996) 806–814
8. Burgess A.E.: High level visual decision efficiencies, In Blakemore, C. (ed.) Vision: Coding and Efficiency. Cambridge Univ. Press,: London (1990) 431–440
9. Barrett, H.H., Yao, J., Rolland, J.P., Myers, K.J.: Model observers for assessment of image quality. Proc. Nat. Acad. Sci. USA 90 (1993) 9758–9765
10. Abbey, C.K., Bochud, F.O.: Modeling visual signal detection tasks in correlated image noise with linear observer models. In Beutel, J., Kundel, H., vanMetter, R.L. (eds.) Handbook Of Medical Imaging: Physics and Psychophysics. SPIE Press,: Bellingham (2000) 629–654
11. Eckstein, M.P., Abbey, C.K., Bochud, F.O.: A practical guide to model observers for visual detection in synthetic and natural noisy images. In Beutel, J., Kundel, H.L., van Metter, R.L. (eds.) Handbook of Medical Imaging. SPIE Press,: Bellingham (2000) 593–628
12. Wagner, R.F., Brown, D.G.: Unified SNR analysis of medical imaging systems. Phys. Med. Biol. 30 (1985) 489–518
13. Myers, K.J.: Ideal observer models of visual signal detection. In Beutel, J., Kundel, H., van Metter, R.L. (eds.) Handbook Of Medical Imaging: physics and Psychophysics. SPIE Press,: Bellingham (2000) 558–592
14. Fiete, R.D., Barrett, H.H., Smith, W.E., Myers, K.J.: Hotelling trace criterion and its correlation with human-observer performance. J. Opt. Soc. Am. A4 (1987) 945–953
15. Wilson, H., Bergen, J.: A four-mechanism model for threshold spatial vision. Vision Res. 19 (1979) 19–32
16. Barrett, H.H., Abbey, C.K., Gallas, B., Eckstein, M.P.: Stabilized estimates of Hotelling observer detection performance in patient structured noise. Proc. SPIE 3340 (1998) 27–43
17. Burgess A.E., Li, X., Abbey, C.K.: Visual signal detectability with two noise components: anomalous masking effects. J. Opt. Soc. Am. A14 (1997) 2420–2442
18. Burgess A.E., Colborne, B.: Visual signal detection IV: Observer inconsistency. J. Opt. Soc. Am. A5 (1988) 617–627
19. Kundel, H.L., Nodine, C.F., Toto, L., Lauver, S.: A circle cue enhances detection of simulated masses on mammographic backgrounds. Proc. SPIE 3032 (1997) 81–84
20. Burgess A.E., Chakraborty, S.: Producing lesions for hybrid images: extracted tumours and simulated microcalcifications. Proc. SPIE 3663 (1999) 316–322
21. Bendat, J.S., Piersol, A.G.: Random Data: analysis and measurement procedures. John Wiley & Sons, New York (1986)
22. Press, W.H., Flannery, B.P., Teukolsky, S.A., Vettering, W.T.: Numerical Recipes in Fortran. Second Edition. Cambridge Univ. Press, (1992)
23. Burgess A.E.: Mammographic structure: Data preparation and spatial statistics analysis. Proc. SPIE 3661 (1999) 642–653
24. C.K. Abbey: Assessment of reconstructed images, Ph.D. Dissertation, Univ. of Arizona, 1998.
25. Burgess A.E.: Evaluation of detection model performance in power-law noise. Proc. SPIE 4324 (2001), (in press)
26. Burgess A.E., Jacobson, F.L., Judy, P.F.: On the detection of lesions in mammographic structure. Proc. SPIE 3663 (1999) 304–315
27. Rosenberg, R.D., Hunt, W.C., Williamson, M.R., et al.: Effects of age, breast density, ethnicity, and estrogen replacement therapy on screening mammographic sensitivity and cancer stage at diagnosis: review of 183,134 screening mammograms in Albuquerque, New Mexico, Radiology 209, (1998), 511–518
28. Burgess A.E., Jacobson, F.L., Judy, P.F.: Breast parenchymal patterns: Human observer lesion detection experiments. Med. Phys. (in press)