Observer performance evaluation of a method of simulating abnormalities in mammograms

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 4686, Issue , 2002, Pages 263-272

  Chakraborty, Dev P ^a   Conant, Emily F ^a   Johnson, Jeffrey P ^b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b SARNOFF CORPORATION   (United States)

Author keywords

Digital; Mammography; Microcalcification; Modality evaluation; ROC; Simulations

Indexed keywords

COMPUTER SIMULATION; DIAGNOSIS; PROBABILITY; RADIOLOGY;

MODALITY EVALUATION;

MAMMOGRAPHY;

EID: 0036031454     PISSN: 0277786X     EISSN: None     Source Type: Journal    
DOI: 10.1117/12.462686     Document Type: Article

References (18)

1. Begg C.B., McNeil B.J. Assessment of Radiologic Tests: Control of Bias and Other Design Considerations. Radiology 1988; 167:565-569.
2. Heath M., Bowyer K., Kopans D., Moore, R., Kegelmeyer-Jr P. The Digital Database for Screening Mammography. In: Yaffe M., ed. IWDM 2000: 5th International Workshop on Digital Mammography. Madison, WI: Medical Physics, 2001:212-218.
3. Bisogni G., Bottigli U., Ceccopieri, et al. The CALMA Mammographs Database: Image Collection and CAD Tools for Spiculated Lesions Detection and Texture Classification. In: Yaffe M., ed. IWDM 2000, 5th International Workshop on Digital Mammography. Madison, WI: Medical Physics, 2001.
4. Lado M.J., Tahoces P., Souto M., Mendez A., Vidal J. Real and Simulated clustered microcalcifications in digital mammograms, ROC study of observer performance. Medical Physics 1997; 24(9):1385-94.
5. Lefebvre F., Benali H., Gilles R., Di Paola R. A simulation model of clustered breast microcalcifications. Med Phys 1994; 21:1865-74.
6. Kallergi M., Gavrielides M.A., He L., Berman C.G., Kim J.J., Clark R.A. Simulation model of mammographic calcifications based on the American College of Radiology Breast Imaging Reporting and Data System, or BIRADS. Acad Radiol 1998; 5:670-9.
7. Nappi J., Dean P.B., Nevalainen O., Toikkanen S. Algorithmic 3D simulation of breast calcifications for digital mammography. Computer Methods and Programs in Biomedicine 2001; 66:115-124.
8. Bakic P.R., Albert M., Maidment A.D.A., Brzakovic D. Evaluation of a Mammography Simulation. In: Yaffe M., ed. IWDM 2000. Madison, WI: Medical Physics, 2000.
9. Burgess A.E., Li, X., Abbey C.K. Visual signal detectability with two noise components: anomalous masking effects. Journal Opt. Soc. Am. A 1997; 14:2420-2442.
10. Burgess A.E., Jacobson F.L., Judy P.F. Human observer detection experiments with mammograms and power-law noise. Med Phys 2001; 28:419-37.
11. Heine J.J., Velthuizen R.P. A statistical methodology for mammographic density detection. Med Phys 2000; 27:2644-51.
12. Burgess A., Xing L., Abbey C. Nodule detection in two component noise: toward patient structure. SPIE: 1997; 3036:2-13.
13. Chakraborty D.P., Kundel H. Anomalous nodule visibility effects in mammographic images, SPIE Medical Imaging 2001: Image Perception and Performance, San Diego, CA, 6/2001,2001. Vol. 4324. SPIE.
14. Chakraborty D.P., Liu X., OShea M., Toto L. A Quantitative Method for Visual Phantom Image Quality Evaluation, SPIE, San Diego, CA, 2000. Vol. 3981. SPIE.
15. Byng J.W., Critten J.P., Yaffe M.J. Thickness-equalization processing for mammographic images. Radiology 1997; 203:564-8.
16. Keshavmurthy S.P., Goodsitt M.M., Chan H.P., Helvie M.A., Christodoulou E. Design and evaluation of an external filter technique for exposure equalization in mammography. Med Phys 1999; 26:1655-69.
17. Johnson J.P., Lubin J., Nafziger J., Chakraborty D. Visual Discrimination Modeling of Lesion Detectability, SPIE Medical Imaging 2002, San Diego, 2002. SPIE.
18. Macmillan N.A., Creelman C.D. Detection Theory: A User's Guide. New York: Cambridge University Press, 1991.