Skin Cancer pp 523-528 | Cite as

Automated Content-Based Image Retrieval: Application on Dermoscopic Images of Pigmented Skin Lesions

  • Alfonso Baldi
  • Raffaele Murace
  • Emanuele Dragonetti
  • Mario Manganaro
  • Stefano Bizzi
Chapter
Part of the Current Clinical Pathology book series (CCPATH)

Abstract

Dermoscopy (dermatoscopy, epiluminescence microscopy) is a noninvasive diagnostic technique for the in vivo observation of pigmented skin lesions (PSLs). This diagnostic tool permits the recognition of morphologic structures not visible by the naked eye, thus opening a new dimension in the analysis of the clinical morphologic features of PSLs. Due to the difficulty and variability of human interpretation, computerized analysis of dermoscopy images has become an important research area in the last years. Recently, numerous systems designed to provide computer-aided analysis of digital images have been reported in literature. The goal of this chapter is to focus on the most recent approaches based on content-based image retrieval systems (CBIR).

Notes

Acknowledgments

This work was supported by a grant from FUTURA-onlus to A.B. and by a grant from Regione Lazio (Legge 598/94 grant MCC-1792) to Advanced Computer System. A.B., R.M., and E.D. are scientific advisers of Advanced Computer System.

Glossary

Content-based image retrieval (CBIR)

also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases.

Dermoscopy

A noninvasive diagnostic technique for the early diagnosis of melanoma and the evaluation of other pigmented and nonpigmented lesions on the skin that are not as well seen with the unaided eye.

References

  1. 1.
    Nathan FE, Mastrangelo MJ. Systemic therapy in melanoma. Semin Surg Oncol. 1998;14:319–27.PubMedCrossRefGoogle Scholar
  2. 2.
    Soengas MS, Lowe SW. Apoptosis and melanoma chemoresistance. Oncogene. 2003;22:3138–51.PubMedCrossRefGoogle Scholar
  3. 3.
    Campioni M, Santini D, Tonini G, Murace R, Dragonetti E, Spugnini EP, Baldi A. Role of Apaf-1, a key regulator of apoptosis, in melanoma progression and chemoresistance. Exp Dermatol. 2005;14:811–8.PubMedCrossRefGoogle Scholar
  4. 4.
    Helmbach H, Rossmann E, Kern MA, Schadendorf D. Drug-resistance in human melanoma. Int J Cancer. 2001;93:617–22.PubMedCrossRefGoogle Scholar
  5. 5.
    Lens MB, Dawes M. Global perspectives of contemporary epidemiological trends of cutaneous malignant melanoma. Br J Dermatol. 2004;150:179–85.PubMedCrossRefGoogle Scholar
  6. 6.
    Schaffer JV, Rigel DS, Kopf AW, Bolognia JL. Cutaneous melanoma: past, present, and future. J Am Acad Dermatol. 2004;51:S65–9.PubMedCrossRefGoogle Scholar
  7. 7.
    Soyer HP, Argenziano G, Zalaudek I, Corona R, Sera F, Talamini R, Barbato F, Baroni A, Cicale L, Di Stefani A, Farro P, Rossiello L, Ruocco E, Chimenti S. Three-point checklist of dermoscopy. A new screening method for early detection of melanoma. Dermatology. 2004;208:27–31.PubMedCrossRefGoogle Scholar
  8. 8.
    Binder M, Schwarz M, Winkler A, et al. A useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists. Arch Dermatol. 1995;131:286–91.PubMedCrossRefGoogle Scholar
  9. 9.
    Argenziano G, Fabbrocini G, Carli P, De Giorgi V, Sammarco E, Delfino M. Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis. Arch Dermatol. 1998;134:1563–70.PubMedCrossRefGoogle Scholar
  10. 10.
    Scott Henning MJ, Dusza SW, Wang SQ, Marghoob AA, Rabinovitz HS, Polsky D, Kopf AW. The CASH (color, architecture, symmetry, and homogeneity) algorithm for dermoscopy. J Am Acad Dermatol. 2007;56:45–52.PubMedCrossRefGoogle Scholar
  11. 11.
    Massone C, Di Stefani A, Soyer HP. Dermoscopy for skin cancer detection. Curr Opin Oncol. 2005;17:147–53.PubMedCrossRefGoogle Scholar
  12. 12.
    Perrinaud A, Gaide O, French LE, Saurat JH, Marghoob AA, Braun RP. Can automated dermoscopy image analysis instruments provide added benefit for the dermatologist? A study comparing the results of three systems. Br J Dermatol. 2007;157:926–33.PubMedCrossRefGoogle Scholar
  13. 13.
    Boldrick JC, Layton CJ, Nquyen J, Swetter SM. Evaluation of digital dermoscopy in a pigmented lesion clinic: clinician versus computer assessment of malignancy risk. J Am Acad Dermatol. 2007;56:417–21.PubMedCrossRefGoogle Scholar
  14. 14.
    Burroni M, Sbano P, Cevenini G. Dysplastic naevus vs. in situ melanoma: digital dermoscopy analysis. Br J Dermatol. 2005;152:679–84.PubMedCrossRefGoogle Scholar
  15. 15.
    Hoffmann K, Gambichler T, Rick A, Kreutz M, Anschuetz M, Grünendick T, Orlikov A, Gehlen S, Perotti R, Andreassi L, Newton Bishop J, Césarini JP, Fischer T, Frosch PJ, Lindskov R, Mackie R, Nashan D, Sommer A, Neumann M, Ortonne JP, Bahadoran P, Penas PF, Zoras U, Altmeyer P. Diagnostic and neural analysis of skin cancer (DANAOS). A multicentre study for collection and computer-aided analysis of data from pigmented skin lesions using digital dermoscopy. Br J Dermatol. 2003;149:801–9.PubMedCrossRefGoogle Scholar
  16. 16.
    Burroni M, Corona R, Dell’Eva G, Sera F, Bono R, Puddu P, Perotti R, Nobile F, Andreassi L, Rubegni P. Melanoma computer-aided diagnosis: reliability and feasibility study. Clin Cancer Res. 2004;10:1881–6.PubMedCrossRefGoogle Scholar
  17. 17.
    Gerger A, Pompl R, Smolle J. Automated epiluminescence microscopy: tissue computer analysis using CART and 1-NN in the diagnosis of melanoma. Skin Res Technol. 2003;9:105–10.PubMedCrossRefGoogle Scholar
  18. 18.
    Oka H, Hashimoto M, Iyatomi H, Argenziano G, Soyer HP, Tanaka M. Internet-based program for automatic discrimination of dermoscopic images between melanomas and Clark naevi. Br J Dermatol. 2004;150:1041.PubMedCrossRefGoogle Scholar
  19. 19.
    Seidenari S, Pellacani G, Grana C. Computer description of colours in dermoscopic melanocytic lesion images reproducing clinical assessment. Br J Dermatol. 2003;149:523–9.PubMedCrossRefGoogle Scholar
  20. 20.
    Emre Celebi M, Iyatomi H, Schaefer G, Stoecker WV. Lesion border detection in dermoscopy images. Comput Med Imaging Graph. 2009;33:148–53.PubMedCrossRefGoogle Scholar
  21. 21.
    Long LR, Antani S, Deserno TM, Thoma GR. Content-based image retrieval in medicine: retrospective assessment, state of the art, and future directions. Int J Health Inf Syst Inform. 2009;4:1–16.CrossRefGoogle Scholar
  22. 22.
    Zhu Y, Huang X, Wang W, Lopresti D, Long R, Antani S, Xue Z, Thoma G. Balancing the role of priors in multi-observer segmentation evaluation. J Signal Process Syst. 2008;55:185–207.PubMedCrossRefGoogle Scholar
  23. 23.
    Uwimana E, Ruiz ME. Integrating an automatic classification method into the medical image retrieval process. AMIA Annu Symp Proc. 2008;6:747–51.Google Scholar
  24. 24.
    Jain R. NSF workshop on visual information management systems. NSF workshop report, Redwood, 24–25 Feb 1992.Google Scholar
  25. 25.
    Smeulders AWM, Worring M, Santini S, Gupta A, Jain R. Content-based image retrieval at the end of the early years. IEEE Trans Pattern Anal Mach Intell. 2000;22:1349–58.CrossRefGoogle Scholar
  26. 26.
    Müller H, Michoux N, Bandon D, Geissbuhler A. A review of content-based image retrieval systems in medical applications-clinical benefits and future directions. Int J Med Inform. 2004;73:1–23.PubMedCrossRefGoogle Scholar
  27. 27.
    Schmid-Saugeons P, Guillod J, Thiran JP. Towards a computer-aided diagnosis system for pigmented skin lesions. Comput Med Imaging Graph. 2003;27:65–78.CrossRefGoogle Scholar
  28. 28.
    Dorileo EAG, Frade MAC, Roselino AMF, Rangayyan RM, Azevedo-Marques PM. Color image processing and content-based image retrieval techniques for the analysis of dermatological lesions. In: 30th annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2008), Aug 2008. p. 1230–3.Google Scholar
  29. 29.
    Wollina U, Burroni M, Torricelli R, Gilardi S, Dell’Eva G, Helm C, Bardey W. Digital dermoscopy in clinical practise: a three-centre analysis. Skin Res Technol. 2007;13:133–42 (10).PubMedCrossRefGoogle Scholar
  30. 30.
    Rahman MM, Desai BC, Bhattacharya P. Image retrieval-based decision support system for dermatoscopic images. In: IEEE symposium on computer-based medical systems, Los Alamitos, IEEE Computer Society, 2006, p. 285–90.Google Scholar
  31. 31.
    Baldi A, Murace R, Dragonetti E, Manganaro M, Guerra O, Bizzi S, Galli L. Definition of an automated Content-based Image Retrieval (CBIR) system for the comparison of dermoscopic images of pigmented skin lesions. Biomed Eng Online. 2009;8:18.PubMedCrossRefGoogle Scholar
  32. 32.
    Baldi A, Quartulli M, Murace R, Dragonetti E, Manganaro M, Guerra O, Bizzi S. Cancers. 2010;2:262–73.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Alfonso Baldi
    • 1
    • 2
  • Raffaele Murace
    • 2
  • Emanuele Dragonetti
    • 2
  • Mario Manganaro
    • 3
  • Stefano Bizzi
    • 3
  1. 1.Department of Environmental, Biological and Pharmaceutical Sciences and TechnologiesSecond University of NaplesNaplesItaly
  2. 2.Futura-onlusRomeItaly
  3. 3.Advanced Computer Systems (ACS)RomeItaly

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