Accurate segmentation and contrast measurement of microcalcifications in mammograms: A phantom study

Medical Physics

Volumn 25, Issue 7 I, 1998, Pages 1102-1110

  Veldkamp, Wouter J H ^a   Karssemeijer, Nico ^a  

^a RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

Contrast measurement; Detection; Microcalcifications; Phantom recordings; Segmentation

Indexed keywords

ERROR DETECTION; IMAGE SEGMENTATION; ITERATIVE METHODS; MAMMOGRAPHY; MARKOV PROCESSES; PHANTOMS; X RAY SCREENS;

CLASSIFICATION RESULTS; CLUSTERED MICROCALCIFICATIONS; COMPUTER AIDED DIAGNOSTICS; CONTRAST MEASUREMENTS; MARKOV RANDOM FIELDS; MICROCALCIFICATIONS; PHANTOM STUDIES; SEGMENTATION PERFORMANCE;

CALCIFICATION (BIOCHEMISTRY);

ACCURACY; ARTICLE; CALCIFICATION; COMPUTER ASSISTED DIAGNOSIS; CONTRAST; MAMMOGRAPHY; MEASUREMENT; MODEL; PHANTOM; PRIORITY JOURNAL;

EID: 0031839549     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.598302     Document Type: Article

References (22)

1. R. M. Nishikawa et al, "Performance of automated CAD schemes for the detection and classification of clustered microcalcifications," in Digital Mammography Proceedings of the Second International Workshop on Digital Mammography, York, England, 9-12 July, edited by A. G. Gale, S. M. Astley, D. R Dance, and A Y. Cairns (Elsevier, Amsterdam, 1994).
2. N. Karssemeijer, "Adaptive noise equalization and recognition of microcalcification clusters in mammograms," Int. J. Pattern Recognition Artificial Intell. 7, 1357-1376 (1993).
3. T. Netsch, "A scale-space approach for the detection of clustered microcalcifications in digital mammograms," in Digital Mammography Proceedings of the Third International Workshop on Digital Mammography, Chicago, IL, 9-12 June, edited by K. Doi, M. L. Giger, R. M. Nishikawa, and R. A. Schmidt (Elsevier, Amsterdam, 1996).
4. J. Parker, D. R. Dance, D. H. Davies, L. J. Yeoman, M. J Michell, and S. Humphreys, "Classification of ductal carcinoma in-situ by image analysis of calcifications from mammograms," Proc. SPIE 1905, 832-840 (1993).
5. W. Zhang, K. Doi, M L. Giger, R. M. Nishikawa, and R. A. Schmidt, "An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms," Med. Phys. 4, 595-601 (1996).
6. R. N. Strickland and H Il. Hahn, "Wavelet transforms for detecting microcalcifications in mammograms," IEEE Trans. Med. Imaging 15, 218-229 (1996)
7. H. P. Chan, B. Sahiner, K. Leung Lam, and M A. Helvie, "Effects of pixel size on classification of microcalcifications on digitized mammograms," Proc. SPIE 2710, 30-41 (1996).
8. F. Levebvre, R. Gilles, J. Masselot, and E. Kahn, "Computer characterization of clustered microcalcifications in mammograms," in Computer Assisted Radiology Proceedings of the International Symposium, Berlin, Germany, edited by H. U. Lumke, M. L. Rhodes, C. C. Jaffe, and R. Felix (Springer, Berlin, 1991).
9. Y. Jiang, R. M. Nishikawa, D. E. Wolverton, C. E. Metz, M L Giger, R. A. Schmidt, C. J. Vyborny, and K. Doi, "Malignant and benign clustered microcalcifications: Automated feature analysis and classification," Radiology 198, 671-678 (1996).
10. J. Parker, D. R. Dance, and J. Suckling, "The hysteresis technique for detection of calcifications in digital mammograms," in Ref. 1.
11. J. Dengler, S. Behrens, and J. F. Desaga, "Segmentation of microcalcifications in mammograms," IEEE Trans. Med. Imaging 12, 634-642 (1993).
12. I. Brodie and A. Gutcheck, "Radiographic information theory and application to mammography," Med. Phys. 9, 79-95 (1982).
13. A. D. A. Maidment, M. Albert, E. F. Conant, and S. A. Feig, "Three-dimensional calcification reconstruction from a limited number of views," Proc SPIE 2708, 378-389 (1996)
14. W. J. H. Veldkamp and N Karssemeijer, "Influence of segmentation on classification of microcalcifications in digital mammography," 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1996 (unpublished).
15. N. Karssemeijer and M. A. O. Thijssen, "Determination of contrast-detail curves of mammography systems by automated image analysis," in Ref. 3.
16. P. K Sahoo, S. Soltani, A. K. C. Wong, and Y. C Chen, "A survey of thresholding techniques," Comput. Vis. Graph. Image Process. 41, 233-260 (1988).
17. R. M. Nishikawa et al., "Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms," Proc. SPIE 1898, 422-429 (1993).
18. B. D. Ripley, "Statistics, images, and pattern recognition," Can. J. Statist. 14, 83-111 (1986).
19. J. Besag, "Statistics, on the statistical analysis of dirty pictures," J. Statist. Soc. B 48, 259-302 (1986).
20. J. H. Hubbell, "Photon mass attenuation and Energy-absorption coefficients from 1 keV to 20 MeV," Int. J. Appl. Radiat. Isot. 33, 1269-1290 (1982).
21. G. T. Barnes and D. P. Chakraborty, "Radiographic mottle and patient exposure in mammography," Radiology 145, 815-821 (1982).
22. R. C. Gonzalez and P. Wintz, Digital Image Processing, 4th ed. (Addison-Wesley, Reading, MA, 1987).