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Information Technologies in Biomedicine pp 67–76Cite as

Automatic Detection of Melanomas: An Application Based on the ABCD Criteria

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Part of the Lecture Notes in Computer Science book series (LNBI,volume 7339)

Abstract

This paper proposes and describes an automatic software system to detect and diagnose malignant melanomas. Skin melanoma is the most serious type of skin cancer and one of the most malignant tumors in humans. In the last several years increasing melanoma incidence has been observed worldwide. The aim of the present research project was to design, implement and test an application for early diagnosis of malignant melanomas. The system is based on the commonly used dermoscopic criteria scheme called the ABCD rule of dermoscopy (A stands for Asymmetry, B for border irregularity, C for color and D for diameter) and has been tested on a database of 50 lesions (20 benign lesions and 30 malignant lesions). The results of the preliminary experiments show that the image analysis with computer assistance has the potential of more accurately identifying the dermoscopic lesions.

Keywords

  • melanoma
  • medical image analysis
  • malignant tumor
  • feature extraction

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  • DOI: 10.1007/978-3-642-31196-3_7
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References

  1. Di Leo, G., Paolillo, A., Sommella, P., Fabbrocini, G., Rescigno, O.: A software tool for the diagnosis of melanomas. Automatic implementation of the 7-Point Check List method. In: Instrumentation and Measurement Technology Conference, I2MTC, pp. 886–891. IEEE (2010)

    Google Scholar 

  2. Iyatomi, H., Oka, H., Celebi, M.E., Tanaka, M., Ogawa, K.: Parameterization of Dermoscopic Findings for the Internet-based Melanoma Screening System. In: IEEE Symposium Computational Intelligence in Image and Signal Processing, CIISP 2007, pp. 189–193 (2007)

    Google Scholar 

  3. Di Leo, G., Paolillo, A., Sommella, P., Fabbrocini, G.: A software tool for the diagnosis of melanomas, Automatic implementation of the 7-Point Check List. In: 2010 43rd Hawaii International Conference on System Science, System Sciences, HICSS, pp. 1–10 (2010)

    Google Scholar 

  4. Tanaka, T., Yamada, R., Tanaka, M., Shimizu, K., Tanaka, M., Oka, H.: A study on image diagnosis of melanoma. In: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEMBS 2004, pp. 1597–1600 (2004)

    Google Scholar 

  5. Braun, R., Rabinovitz, H., Oliviero, M., Kopf, A., Saurat, J.: Dermoscopy of pigmented skin lesion. Journal of the American Academy of Dermatology (2005)

    Google Scholar 

  6. Ng, V., Cheung, D.: Measuring asymmetries of skin lesions. In: IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, October 12-15, vol. 5, pp. 4211–4216 (1997)

    Google Scholar 

  7. Motoyama, H., Tanaka, T., Tanaka, M., Oka, H.: Feature of malignant melanoma based on color information. In: SICE 2004 Annual Conference, vol. 1, pp. 230–233 (2004)

    Google Scholar 

  8. Interactive atlas. Dermoscopy tutorial, http://www.dermoscopy.org/atlas/default.asp

  9. Argenziano, G., Soyer, H.P., De Giorgi, V., et al.: Interactive Atlas of Dermoscopy, Milan, Italy. EDRA Medical Publishing & New Media (2002)

    Google Scholar 

  10. Kaminska-Winciorek, G.: Dermatologia cyfrowa, Cornetis (2008)

    Google Scholar 

  11. Capdehourat, G., Corez, A., Bazzano, A., Musé, P.: Pigmented Skin Lesions Classification Using Dermatoscopic Images. In: Bayro-Corrochano, E., Eklundh, J.-O. (eds.) CIARP 2009. LNCS, vol. 5856, pp. 537–544. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

  12. Andrews, R., Bajcar, S., Grzymała-Busse, J.W., Hippe, Z.S., Whiteley, C.: Optimization of the ABCD Formula for Melanoma Diagnosis Using C4.5, a Data Mining System. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 630–636. Springer, Heidelberg (2004)

    CrossRef  Google Scholar 

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Author information

Authors and Affiliations

  1. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Joanna Jaworek-Korjakowska

Authors
  1. Joanna Jaworek-Korjakowska
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Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Ewa Piętka & Jacek Kawa & 

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Jaworek-Korjakowska, J. (2012). Automatic Detection of Melanomas: An Application Based on the ABCD Criteria. In: Piętka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Lecture Notes in Computer Science(), vol 7339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31196-3_7

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  • DOI: https://doi.org/10.1007/978-3-642-31196-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31195-6

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