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Automatic Detection of Blue-Whitish Veil as the Primary Dermoscopic Feature

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10245))

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Abstract

Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Owing to the difficulty and subjectivity of human interpretation, dermoscopy image analysis has become an important research area. One of the most important local structure that is likely to appear in malignant melanoma is the blue-whitish veil. In this article, we present an unsupervised approach to the blue-whitish veil detection in dermoscopy images of pigmented skin lesions based on the analysis of HSV color space. The method is tested on a set of 179 dermoscopy images and the detection error rate is lower than 15%. The results demonstrate that the presented method achieves both fast and accurate blue structure segmentation in dermoscopy images.

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References

  1. Argenziano, G., Soyer, P.H., Giorgio, V.D., Piccolo, D., Carli, P., Delfino, M., Ferrari, A., Hofmann-Wellenhof, R., Massi, D., Mazzocchetti, G., Scalvenzi, M., Wolf, I.H.: Interactive Atlas of Dermoscopy. Book and CD/Web Resource, Edra Medical Publishing and New Media, Milan (2000)

    Google Scholar 

  2. Arroyo, J.L.G., Zapirain, B.G., Zorrilla, A.M.: Blue-white veil and dark-red patch of pigment pattern recognition in dermoscopic images using machine-learning techniques. In: 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 196–201 (2011)

    Google Scholar 

  3. Celebi, M.E., Iyatomi, H., Stoecker, W.V., Moss, R.H., Rabinovitz, H.S., Argenziano, G., Soyer, H.P.: Automatic detection of blue-white veil and related structures in dermoscopy images. Comput. Vis. Pattern Recogn. 32(8), 670–677 (2008)

    Google Scholar 

  4. Environmental Systems Research Institute Inc: ArcMap. 10.3 color model conversion function (2016). http://desktop.arcgis.com

  5. Jaworek-Korjakowska, J.: Computer-aided diagnosis of micro-malignant melanoma lesions applying support vector machines. BioMed Res. Int. 2016, 1–8 (2016)

    Google Scholar 

  6. Jaworek-Korjakowska, J.: Novel method for border irregularity assessment in dermoscopic color images. Comput. Math. Methods Med. 2015, 1–11 (2016)

    Article  Google Scholar 

  7. Kowal, M., Filipczuk, P.: Nuclei segmentation for computer-aided diagnosis of breast cancer. Int. J. Appl. Math. Comput. Sci. 24(1), 19–31 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  8. Kowal, M., Filipczuk, P., Obuchowicz, A., Korbicz, J., Monczak, R.: Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images. Comput. Biol. Med. 43, 1563–1572 (2013)

    Article  Google Scholar 

  9. Leiter, U., Buettner, P.G., Eigentler, T.K., Garbe, C.: Prognostic factors of thin cutaneous melanoma: an analysis of the central malignant melanoma registry of the german dermatological society. J. Clin. Oncol. 22(18), 3660–3667 (2004). PMID: 15302905, http://ascopubs.org/doi/abs/10.1200/JCO.2004.03.074

  10. Leo, G.D., Fabbrocini, G., Paolillo, A., Rescigno, O., Sommella, P.: Toward an automatic diagnosis system for skin lesions: estimation of bluewhitish veil and regression structures. In: 6th International Multi-Conference on Systems, Signals and Devices (2009)

    Google Scholar 

  11. Mayer, J.: Systematic review of the diagnostic accuracy of dermatoscopy in detecting malignant melanoma. Med. J. Aust. 167(4), 206–210 (1997)

    Google Scholar 

  12. Menzies, S.W., Crotty, K.A., Ingwar, C., McCarthy, W.H.: An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy, 2nd edn. McGraw-Hill, Sydney (2002)

    Google Scholar 

  13. Ogorzałek, M., Surówka, G., Nowak, L., Merkwirth, C.: Computational intelligence and image processing methods for applications in skin cancer diagnosis. In: Fred, A., Filipe, J., Gamboa, H. (eds.) Communications in Computer and Information Science. CCIS, vol. 52, pp. 3–20. Springer, Berlin, Heidelberg (2010)

    Google Scholar 

  14. Śmietański, J., Tadeusiewicz, R., Łuczyńska, E.: Texture analysis in perfusion images of prostate cancer a case study. Int. J. Appl. Math. Comput. Sci. 20(1), 149–156 (2010)

    Google Scholar 

  15. Tadeusiewicz, R.: Place and role of intelligent systems in computer science. Comput. Methods Mater. Sci. 10(4), 193–206 (2010)

    Google Scholar 

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Acknowledgements

This work was supported by AGH University of Science and Technology statutory funds (No. 11.11.120.612).

Author information

Authors and Affiliations

  1. Department of Automatics and Biomedical Engineering, AGH University of Science and Technology in Krakow, Kraków, Poland

    Joanna Jaworek-Korjakowska & Paweł Kłeczek

  2. Research Group for Pattern Recognition, University Siegen, Siegen, Germany

    Marcin Grzegorzek & Kimiaki Shirahama

  3. Faculty of Informatics and Communication, University of Economics in Katowice, Katowice, Poland

    Marcin Grzegorzek

Authors
  1. Joanna Jaworek-Korjakowska
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  2. Paweł Kłeczek
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  3. Marcin Grzegorzek
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  4. Kimiaki Shirahama
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Corresponding author

Correspondence to Joanna Jaworek-Korjakowska .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Jaworek-Korjakowska, J., Kłeczek, P., Grzegorzek, M., Shirahama, K. (2017). Automatic Detection of Blue-Whitish Veil as the Primary Dermoscopic Feature. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_58

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  • DOI: https://doi.org/10.1007/978-3-319-59063-9_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59062-2

  • Online ISBN: 978-3-319-59063-9

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