Computerized Medical Imaging and Graphics
Volume 33, Issue 6 , Pages 415-422 , September 2009

A textural approach for mass false positive reduction in mammography

Received 31 October 2008 ,Revised 25 March 2009 ,Accepted 26 March 2009.

References 

  1. Eurostat, Health statistics Atlas on mortality in the European Union, Office for Official Publications of the European Union; 2002.
  2. American Cancer Society Breast cancer: facts and figures. ACS; 2003–2004.
  3. Esteve J, Kricker A, Ferlay J, Parkin D. Facts and figures of cancer in the European Community. In: Tech. rep., International Agency for Research on Cancer. Lyon, France. 1993;
  4. Buseman S, Mouchawar J, Calonge N, Byers T. Mammography screening matters for young women with breast carcinoma. Cancer. 2003;97(2):352–358
  5. Sickles EA. Breast cancer screening outcomes in women ages 40–49: clinical experience with service screening using modern mammography. J Natl Cancer Inst: Monogr. 1997;22:99–104
  6. De Koning HJ, Fracheboud J, Boer R, Verbeek AL, Collette HJ, Hendriks JHCL. Nation-wide breast cancer screening in the Netherlands: support for breast cancer mortality reduction.. National evaluation team for breast cancer screening, Int J Cancer. 1995;60(6):777–780
  7. Hendee WR, Beam C, Hendrick E. Proposition: all mammograms should be double-read. Med Phys. 1999;26:115–118
  8. Thurfjell EL, Lernevall KA, Taube AAS. Benefit of independent double reading in a population-based mammography screening program. Radiology. 1994;191:241–244
  9. Vacek PM, Geller BM, Weaver DL, Foster RS. Increased mammography use and its impact on earlier breast cancer detection in Vermont. Cancer. 2002;94(8):2160–2168
  10. Bird RE, Wallace TW, Yankaskas BC. Analysis of cancers missed at screening mammography. Radiology. 1992;184:613–617
  11. Birdwell RL, Ikeda DM, O’Shaughnessy KD, Sickles EA. Mammographic characteristics of 115 missed cancers later detected with screening mammography and the potential utility of computer-aided detection. Radiology. 2001;219:192–202
  12. Basset LW, Gold RH. Breast Cancer Detection: Mammograms and Other Methods in Breast Imaging. New York: Grune & Stratton; 1987;
  13. Hall FM, Storella JM, Siverstond DZ, Wyshak G. Nonpalpable breast lesions: recommendations for biopsy based on suspicion of carcinoma at mammography. Radiology. 1988;167:353–358
  14. Winsberg F, Elkin M, Macy J, Bordaz V, Weymouth W. Detection of radiographic abnormalities in mammograms by means of optical scanning and computer analysis. Radiology. 1967;89(2):211–215
  15. Freer TW, Ulissey MJ. Screening mammography with computer-aided detection: prospective study of 12860 patients in a community breast center. Radiology. 2001;220:781–786
  16. Zwiggelaar R, Astley SM, Boggis CRM, Taylor CJ. Linear structures in mammographic images: detection and classification. IEEE Trans Med Imag. 2004;23(9):1077–1086
  17. Khoo LAL, Taylor P, Given-Wilson RM. Computer-aided detection in the United Kingdom national breast screening programme: prospective study. Radiology. 2005;237(2):444–449
  18. Nishikawa RM, Kallergi M. Computer-aided detection, in its present form, is not an effective aid for screening mammography. Med Phys. 2006;33:811–814
  19. Taylor P, Champness J, Given-Wilson R, Johnston K, Potts H. Impact of computer-aided detection prompts on the sensitivity and specificity of screening mammography. Health Techn Assess. 2005;9(6):1–58
  20. Sahiner B, Chan HP, Wei D, Petrick N, Helvie MA, Adler DD. Image feature selection by a genetic algorithm: Application to classification of mass and normal breast tissue. Med Phys. 1996;23:1671–1684
  21. Qian W, Sun X, Song D, Clark RA. Digital mammography - wavelet transform and Kalman-filtering neural network in mass segmentation and detection. Acad Radiol. 2001;8(11):1074–1082
  22. Christoyianni I, Koutras A, Dermatas E, Kokkinakis G. Computer aided of breast cancer in digitized mammograms. Comp Med Imag Grap. 2002;26:309–319
  23. Ojala T, Pietikainen M, Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Machine Intell. 2002;24(7):971–987
  24. Oliver A, Lladó X, Freixenet J, Martí J. False positive reduction in mammographic mass detection using local binary patterns. Int Conf Med Image Comput Comput Assist Interv. 2007;4478:286–293
  25. Zhang J, Tan T. Brief review of invariant texture analysis methods. Pattern Recognit. 2002;35(3):735–747
  26. Ahonen T, Hadid A, Pietikainen M. Face detection with local binary patterns: application to face recognition. IEEE Trans Pattern Anal Machine Intell. 2006;28(12):2037–2041
  27. Rangayyan RM, Ayres FJ, Desautels JEL. A review of computer-aided diagnosis of breast cancer: toward the detection of subtle signs. J Frankl Inst. 2007;344(3–4):312–348
  28. Suliga M, Deklerck R, Nyssen E. Markov random field-based clustering applied to the segmentation of masses in digital mammograms. Comp Med Imag Grap. 2008;32(6):502–512
  29. Rojas A, Nandi A. Detection of masses in mammograms via statistically based enhancement, multilevel-thresholding segmentation, and region selection. Comp Med Imag Grap. 2008;32(4):304–315
  30. Wu Y, Wei J, Hadjiiski LM, Sahiner B, Zhou C, Ge J. Bilateral analysis based false positive reduction for computer-aided mass detection. Med Phys. 2007;34(8):3334–3344
  31. van Engeland S, Karssemeijer N. Combining two mammographic projections in a computer aided mass detection method. Med Phys. 2007;34:898–905
  32. Metz CE. Evaluation of digital mammography by ROC analysis. Int Work Dig Mammogr. 1996;61–68
  33. Angelini E, Campanini R, Iampieri E, Lanconelli N, Masotti M, Roffilli M. Testing the performances of different image representations for mass classification in digital mammograms. Int J Mod Phys C. 2006;17(1):113–131
  34. Oliver A, Martí J, Martí R, Bosch A, Freixenet J. A new approach to the classification of mammographic masses and normal breast tissue. IAPR Int Conf Pattern Recognit. 2006;4:707–710
  35. Turk MA, Pentland AP. Eigenfaces for recognition. J Cognitive Neurosci. 1991;3(1):71–86
  36. Oliver A, Lladó X, Martí J, Martí R, Freixenet J. False positive reduction in breast mass detection using two-dimensional PCA. Lect Not Comp Sci. 2007;4478:154–161
  37. Yang J, Zhang D, Frangi AF, Yang J. Two-dimensional PCA: a new approach to appearance-based face representation and recognition. IEEE Trans Pattern Anal Machine Intell. 2004;26(1):131–137
  38. Varela C, Tahoces PG, Méndez AJ, Souto M, Vidal JJ. Computerized detection of breast masses in digitized mammograms. Comput Biol Med. 2007;37(2):214–226
  39. Tourassi GD, Eltonsy NH, Graham JH, Floyd CE, Elmaghraby AS. Feature and knowledge based analysis for reduction of false positives in the computerized detection of masses in screening mammography. IEEE Conf Eng Med Biol Soc. 2005;6524–6527
  40. Chang YH, Hardesty LA, Hakim CM, Chang TS, Zheng B, Good WF. Knowledge-based computer-aided detection of masses on digitized mammograms: a preliminary assessment. Med Phys. 2001;28(4):455–461
  41. Tourassi GD, Vargas-Vorecek R, Catarious DM, Floyd CE. Computer-assisted detection of mammographic masses: A template matching scheme based on mutual information. Med Phys. 2003;30(8):2123–2130
  42. Tourassi GD, Harrawood B, Singh S, Lo JY, Floyd CE. Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms. IEEE Trans Med Imag. 2007;34(1):140–150
  43. Ojala T, Pietikainen M, Harwood D. A comparative-study of texture measures with classification based on feature distributions. Pattern Recognit. 1996;29(1):51–59
  44. Vapnik V. Statistical Learning Theory. New York: John Wiley & Sons; 1998;
  45. Heath M, Bowyer K, Kopans D, Moore R, Kegelmeyer PJ. The digital database for screening mammography. Int Work Dig Mammogr. 2000;212–218

PII: S0895-6111(09)00038-X

doi: 10.1016/j.compmedimag.2009.03.007

Computerized Medical Imaging and Graphics
Volume 33, Issue 6 , Pages 415-422 , September 2009

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