Region-Based Contrast Enhancement of Mammograms

IEEE Transactions on Medical Imaging

Volumn 11, Issue 3, 1992, Pages 392-406

  Morrow, William Mark ^a   Paranj, Raman Bhalachandra ^a   Rangayyan, Rangaraj M ^a   Leo Desautels, Joseph Edward ^b  

^a UNIVERSITY OF CALGARY   (Canada)

^b FOOTHILLS HOSPITAL   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ENHANCEMENT; RADIOGRAPHY; STATISTICAL METHODS;

FIXED-NEIGHBORHOOD STATISTICAL ENHANCEMENT; HISTOGRAM EQUALIZATION; IMAGE CONTRAST ENHANCEMENT; MAMMOGRAPHY; REGION-BASED IMAGE PROCESSING;

MEDICAL IMAGING;

EID: 0026928099     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/42.158944     Document Type: Article

References (50)

1. Canadian Cancer Society, Facts on Breast Cancer, Apr. 1989.
2. E. A. Sickles, “Computed tomography scanning, transillumination, and magnetic resonance imaging of the breast,” Recent Results in Cancer Research, vol. 105, pp. 31–36, 1987.
3. L. W. Bassett and R. H. Gold, Eds., Mammography, Thermography, and Ultrasound in Breast Cancer Detection. New York: Grune and Stratton, 1982.
4. I. Andersson and B. F. Sigfusson, “Screening for breast cancer in Malmo: A randomized trial,” Recent Results in Cancer Research, vol. 105, pp. 62–66, 1987.
5. L. Tabar, A. Gad, L. Holmberg, and U. Ljungquist, “Significant reduction in advanced breast cancer: Results of the first seven years of mammography screening in Kopparberg, Sweden,” Diag. Imaging Clin. Med., vol. 54, pp. 158–164, 1985.
6. E. A. Sickles, “Breast calcifications: Mammographic evaluation,” Radiology, vol. 160, 289–293, 1981.
7. R. Gordon and R. M. Rangayyan, “Radiographic feature enhancement, information content, and dose reduction in mammography and cardiac angiography,” in Proc. IEEE Frontiers Eng. Comput. Health Care, pp. 161–165, 1983.
8. R. Gordon and R. M. Rangayyan, “Feature enhancement of film mammograms using fixed and adaptive neighborhoods,” Appl. Opt., vol. 23, no. 4, pp. 560–564, Feb. 1984.
9. R. M. Rangayyan and H. N. Nguyen, “Pixel-independent image processing techniques for enhancement of features in mammograms,” in Proc. 8th IEEE Eng. Med. Biol. Conf., 1986, pp. 1113–1117.
10. R. M. Rangayyan and H. N. Nguyen, “Pixel-independent image processing techniques for noise removal and feature enhancement,” in IEEE Pacific Rim Conf. Commu., Comput., Signal Processing, IEEE, June 1987, pp. 81–84.
11. W. M. Morrow and R. M. Rangayyan, “Adaptive neighborhood contrast enhancement on a parallel supercomputer,” in Proc. Supercomput. Symp. '90, Montreal, Canada, June 4–6, 1990, pp. 329–334.
12. W. M. Morrow, “Region-based image processing with application to mammography,” M.Sc. thesis, Univ. Calgary, Calgary, Canada, 1990.
13. M. B. McSweeney, P. Sprawls, and R. L. Egan, “Enhanced image mammography,” AJR, vol. 140, pp. 9–14, 1983.
14. H. P. Chan, C. J. Vyborny, H. MacMahon, C. E. Metz, K. Doi, and E. A. Sickles, “Digital mammography: ROC studies of the effects of pixel size and unsharp-mask filtering on the detection of subtle microcalcifications,” Investigative Radiology, vol. 22, no. 7, pp. 581–589, July 1987.
15. R. L. Smathers, E. Bush, J. Drace, M. Stevens, F. G. Sommer, B. W. Brown, and B. Karras, “Mammographic microcalcifications: Detection with xerography, screen-film and digitized film display,” Radiology, vol. 159, no. 3, pp. 673–677, June 1986.
16. F. Winsberg, M. Elkin, Jr. J. Macy, V. Bordaz, and W. Weymouth, “Detection of radiographic abnormalities in mammograms by means of optical scanning and computer analysis,” Radiology, vol. 89, pp. 211–215, 1967.
17. J. L. Semmlow, A. Shadagopappan, L. V. Ackerman, W. Hand, and F. S. Alcorn, “A fully automated system for screening xeromammograms,” Comput. Biomed Res., vol. 13, pp. 350–362, 1980.
18. C. Kimme, B. J. O'Loughlin, and J. Sklansky, Data Structures, Computer Graphics and Pattern Recognition. New York: Academic, 1977, Automatic detection of suspicious abnormalities in breast radiographs, pp. 84–88.
19. S. Lai, X. Li, and W. F. Bischof, “On techniques for detecting circumscribed masses in mammograms,” IEEE Trans. Med. Imaging, vol. 8, pp. 377–386, Dec. 1989.
20. D. Brzakovic, X. M. Luo, and K. Brzakovic, “An approach to automated detection of tumors in mammograms,” IEEE Trans. Med. Imaging, vol. 9, pp. 233–241, Sept. 1990.
21. W. Spiesberger, “Mammogram inspection by computer,” IEEE Trans. Biomed. Eng., vol. BME-26, pp. 213–219, Apr. 1979.
22. W. G. Wee, M. Moskowitz, N. C. Chang, V. C. Ting, and S. Pemmeraju, “Evaluation of mammographic calcification using a computer program,” Radiology, vol. 116, pp. 717–720, 1975.
23. H. P. Chan, K. Doi, S. Galhotra, C. J. Vybomy, H. MacMahon, and Peter M. Jokich, “Image feature analysis and computer-aided diagnosis in digital radiography, i. Automated detection of microcalcifications in mammography,” Med. Phys., vol. 14, no. 4, pp. 538–548, July/Aug. 1987.
24. H. P. Chan, K. Doi, C. J. Vyborny, K. L. Lam, and R. A. Schmidt, “Computer-aided detection of microcalcifications in mammograms: Methodology and preliminary clinical study,” Investigative Radiology, vol. 23, no. 9, pp. 664–671, Sept. 1988.
25. H. P. Chan, K. Doi, C. J. Vyborny, R. A. Schmidt, C. E. Metz, K. L. Lam, T. Ogura, Y. Wu, and H. MacMahon, “Improvement in radiologists detection of clustered microcalcifications on mammograms,” Investigative Radiology, vol. 25, no. 10, pp. 1102–1110, Oct. 1990.
26. L. V. Ackerman and E. Gose, “Breast lesion classification by computer and xeroradiography,” Cancer, vol. 30, pp. 1025–1035, 1972.
27. L. V. Ackerman, A. N. Mucciardi, E. E. Gose, and F. S. Alcorn, “Classification of benign and malignant breast tumors on the basis of 36 radiographic properties,” Cancer, vol. 31, pp. 342–352, 1973.
28. H. M. Cook and M. D. Fox, “Artificial intelligence applied to mammographic image analysis,” in Electron. Imaging '87 Conf., Boston, MA, Nov. 1987.
29. E. L. Hall, Computer Image Processing and Recognition. New York: Academic, 1979.
30. R. C. Gonzalez and P. Wintz, Digital Image Processing. Reading, MA: Addison-Wesley, 1987, 2nd ed.
31. A. Rosenfeld and A. C. Kak, Digital Picture Processing, Volume 1. New York: Academic, 1982.
32. S. M. Pizer, E. P. Ambum, D. D. Austin, R. Cromartie, A. Geselowitz, T. Geer, B. tar Haar Remeny, J. B. Zimmerman, and K. Zuiderveld, “Adaptive histogram equalization and its variations,” Comput. Vision, Graph. Image Processing, vol. 39, pp. 355–368, 1987.
33. J. B. Zimmerman, S. M. Pizer, E. V. Staab, J. R. Perry, W. McCartney, and B. C. Brenton, “An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement,” IEEE Trans. Med. Imaging, vol. 7, pp. 304–312, Dec. 1988.
34. J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-2, pp. 165–168, Mar. 1980.
35. P. M. Narendra and R. C. Fitch, “Real-time adaptive contrast enhancement,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-3, pp. 655-661 November 1981.
36. J. Rogowska, K. Preston, and D. Sashin, “Evaluation of digital unsharp masking and local contrast stretching as applied to chest radiographs,” IEEE Trans. Biomed. Eng., vol. 35, pp. 817–827, Oct. 1988.
37. M. I. Sezan, A. M. Tekalp, and R. Schaetzing, “Automatic anatomically selective image enhancement in digital chest radiography,” IEEE Trans. Med. Imaging, vol. 8, pp. 154–162, June 1989.
38. J. S. DaPonte and M. D. Fox, “Enhancement of chest radiographs with gradient operators,” IEEE Trans. Med. Imaging, vol. 7, pp. 109–117, June 1988.
39. D. H. Ballard and C. M. Brown, Computer Vision. Englewood Cliffs, NJ: Prentice-Hall, 1982.
40. R. H. Johnson, A. C. Nelson, R. M. Haralick, and M. M. Goodsitt, “Optimal information retrieval from complex low frequency backgrounds in medical images,” in IEEE Eng. Med. Biology Soc. 11th Annu. Conf., IEEE, 1989, pp. 384–385.
41. A. P. Dhawan, E. Le Royer, and R. Gordon, “Adaptive neighborhood image processing for feature enhancement of mammograms,” in Proc. 8th Annu. Conf. IEEE Eng. Med. Biology Soc., 1986, pp. 1096–1100.
42. A. P. Dhawan, G. Buelloni, and R. Gordon, “Enhancement of mammographic features by optimal adaptive neighborhood image processing,” IEEE Trans. Med. Imaging, vol. MI-5, pp. 8–15, Mar. 1986.
43. A. P. Dhawan and E. LeRoyer, “Mammographic feature enhancement by computerized image processing,” Comput. Methods Programs Biomed., vol. 27, no. 1, pp. 23–35, 1988.
44. A. Beghdadi and A. Le Negrate, “Contrast enhancement technique based on local detection of edges,” Comput. Vision, Graph. Image Processing, vol. 46, pp. 162–174, 1989.
45. W. M. Morrow and R. M. Rangayyan, “Feature-adaptive enhancement and analysis of high-resolution digitized mammograms,” in Proc. 12th IEEE Eng. Med. Biology Conf., 1990, pp. 165–166.
46. T. Pavlidis, Algorithms for Graphics and Image Processing. Rockville, MD: Computer Science, 1982.
47. J. D. Foley, A. van Dam, S. K. Feiner, and J. F. Hughes, Computer Graphics: Principles and Practice. Reading, MA: Addison-Wesley, 1990.
48. P. Heckbert, Graphics Gems. New York: Academic, 1990.
49. G. R. Kuduvalli and R. M. Rangayyan, “Performance analysis of reversible image compression techniques for high resolution digital teleradiology,” IEEE Trans. Med. Imaging, see this issue.
50. R. B. Paranjape, W. M. Morrow, H. N. Nguyen, and R. M. Rangayyan, “Adaptive neighborhood image processing,” Appl. Opt., submitted for publication.