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Contrast Enhancement in Dense Breast Images to Aid Clustered Microcalcifications Detection

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This paper presents a method to provide contrast enhancement in dense breast digitized images, which are difficult cases in testing of computer-aided diagnosis (CAD) schemes. Three techniques were developed, and data from each method were combined to provide a better result in relation to detection of clustered microcalcifications. Results obtained during the tests indicated that, by combining all the developed techniques, it is possible to improve the performance of a processing scheme designed to detect microcalcification clusters. It also allows operators to distinguish some of these structures in low-contrast images, which were not detected via conventional processing before the contrast enhancement. This investigation shows the possibility of improving CAD schemes for better detection of microcalcifications in dense breast images.

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References

  1. ML Giger (2000) ArticleTitleComputer-aided diagnosis of breast lesions in medical images Comput Sci Eng 2 IssueID5 39–45 Occurrence Handle10.1109/5992.877391

    Article  Google Scholar 

  2. ML Giger H MacMahon (1996) ArticleTitleImage processing and computer-aided diagnosis Radiol Clin North Am 34 IssueID3 565–595 Occurrence Handle8657872 Occurrence Handle1:STN:280:BymB387ptVc%3D

    PubMed  CAS  Google Scholar 

  3. M LeGal G Chavanne D Pellier (1984) ArticleTitleValeur diagnostique des microcalcifications groupées découvertes par mammographies Bull Cancer 71 57–64 Occurrence Handle1:STN:280:BiuC2sblsVc%3D

    CAS  Google Scholar 

  4. RM Nishikawa Y Jiang ML Giger RA Schimdt CJ Vyborny W Zhang J Papaionnou U Bick R Nagel K Doi (1994) Performance of automated CAD schemes for the detection and classification of clustered microcalcifications AG Gale (Eds) et al. Digital Mammography Elsevier Amsterdam 13–20

    Google Scholar 

  5. Roerih J, et al.: Clinical results with R2 imagechecker system. In: Karssemeijer N, et al. (Eds). Digital Mammography. Kluwer Academic Publishing, Dordrecht, The Netherlands, 1998, pp 395–400

  6. F Schmidt E Sorantin C Szepesvari E Graif M Becker H Mayer K Hartwagner (1999) ArticleTitleAn automatic method for the identification and interpretation of clustered microcalcifications in mammograms Phys Med Biol 44 1231–1243 Occurrence Handle10368015 Occurrence Handle10.1088/0031-9155/44/5/011 Occurrence Handle1:STN:280:DyaK1M3psVCrsw%3D%3D

    Article  PubMed  CAS  Google Scholar 

  7. JK Kim HW Park (1999) ArticleTitleStatistical textural features for detection of microcalcifications in digitized mammograms IEEE Trans Med Imag 18 IssueID3 231–237 Occurrence Handle10.1109/42.764896 Occurrence Handle1:STN:280:DyaK1M3ptVeluw%3D%3D

    Article  CAS  Google Scholar 

  8. MA Gavrielides JY Lo R Vargas-Voracek R CE Floyd (1999) ArticleTitleSegmentation of suspicious clustered microcalcifications in mammograms Med Phys 27 IssueID1 13–22 Occurrence Handle10.1118/1.598852

    Article  Google Scholar 

  9. T Netsch H-O Peitgen (1999) ArticleTitleScale-space signatures for the detection of clustered microcalcifications in digital mammograms IEEE Trans Med Imag 18 IssueID9 774–786 Occurrence Handle10.1109/42.802755 Occurrence Handle1:STN:280:DC%2BD3c%2Fjs1Wlsg%3D%3D

    Article  CAS  Google Scholar 

  10. S Yu L Guan (2000) ArticleTitleA CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films IEEE Trans Med Imag 19 IssueID2 115–126 Occurrence Handle10.1109/42.836371 Occurrence Handle1:STN:280:DC%2BD3c3ksVyluw%3D%3D

    Article  CAS  Google Scholar 

  11. NF Boyd JW Byng RA Jong EK Fishell LE Little AB Miller GA Lockwood DL Tritchler MJ Yaffe (1995) ArticleTitleQuantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening study J Natl Cancer Inst 87 670–675 Occurrence Handle7752271 Occurrence Handle10.1093/jnci/87.9.670 Occurrence Handle1:STN:280:ByqB2s7ntVQ%3D

    Article  PubMed  CAS  Google Scholar 

  12. H Schiabel FLS Nunes PM Azevedo Marques AF Frere (1997) ArticleTitleA computerized scheme for detection of clusters of microcalcifications by mammograms image processing Med Biol Eng Comput 35 IssueIDsuppl 2 705

    Google Scholar 

  13. A Raji A Thaibaoui E Petit V Bunel G Mimoun (1998) ArticleTitleA gray-level transformation-based method for image enhancement Pattern Recogn Lett 19 1207–1212 Occurrence Handle10.1016/S0167-8655(98)00109-3

    Article  Google Scholar 

  14. Nunes FLS, Schiabel H, Benatti RH, Stamato RC, Escarpinati MC, Goes CE: A method to contrast enhancement of digital dense breast images aimed to detect clustered microcalcifications. In: 2001 International Conference on Image Processing, Thessaloniki, Greece, October 7–10, 2001

  15. RM Nishikawa ML Giger K Doi CJ Vyborny RA Schmidt (1993) ArticleTitleComputer-aided detection of clustered microcalcifications: an improved method for grouping detected signals Med Phys 20 IssueID6 1661–1666 Occurrence Handle8309438 Occurrence Handle10.1118/1.596952 Occurrence Handle1:STN:280:ByuC2c3mvF0%3D

    Article  PubMed  CAS  Google Scholar 

  16. Nunes FLS, Schiabel H, Benatti R: Application of image processing techniques for enhancement in dense breasts digital mammograms. In: Medical Imaging 1999 of The International Society for Optical Engineering—SPIE: 1105–1116 San Diego, CA, USA, February 20–26, 1999

  17. Schiabel H, Nunes FLS, Escarpinati M, Benatti R: Performance of a processing scheme for clustered microcalcifications: detection with different images database. In: World Congress on Med Phys and Biomedical Engineering, 2000 Chicago (USA), July 23–28, 2000

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Acknowledgments

The authors are grateful to Hospital das Clínicas at Ribeirão Preto (SP), Brazil, which allowed us to use the mammograms in the tests, with special thanks to the personnel from the section of X-ray image archives in that hospital. They are also grateful to FAPESP, which provided financial support to this research, and to Prof. Oswaldo N. Oliveira Jr. for his critical reading of the manuscript and suggestions.

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Authors and Affiliations

  1. Programa de Pós-Graduação em Ciência da Computação, Centro Universitário Eurípides de Marília, Av. Hygino Muzzi Filho, 529-Campus Universitário, 17525-901, Marília, SP, Brazil

    Fátima L. S. Nunes

  2. Departamento de Engenharia Elétrica, EESC, Universidade de São Paulo, Av. Trabalhador Saocarlense, 400-13566-590, São Carlos, SP, Brazil

    Homero Schiabel & Claudio E. Goes

  3. Fundação de Ensino Eurípides Soares da Rocha de Marília, Av. Hygino Muzzi Filho, 529 Campus Universitário, CEP 17525-901, Cx. Postal 2041, Marília, SP, Brazil

    Fátima L. S. Nunes

Authors
  1. Fátima L. S. Nunes
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  2. Homero Schiabel
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  3. Claudio E. Goes
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Correspondence to Fátima L. S. Nunes.

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Nunes, F.L.S., Schiabel, H. & Goes, C.E. Contrast Enhancement in Dense Breast Images to Aid Clustered Microcalcifications Detection. J Digit Imaging 20, 53–66 (2007). https://doi.org/10.1007/s10278-005-6976-5

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  • DOI: https://doi.org/10.1007/s10278-005-6976-5

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