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Further Research on Automatic Estimation of Asymmetry of Melanocytic Skin Lesions

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Human – Computer Systems Interaction: Backgrounds and Applications 2

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 99))

Abstract

This paper presents a method for automatic identification of asymmetry in digital images containing melanocytic skin lesion. Our method is a part of the new system for classifying skin lesion using Stolz strategy, based on the ABCD rule.

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References

  1. Grzymała-Busse, J.W., Hippe, Z.S., Knap, M., Paja, W.: Infoscience technology: The impact of internet accessible melanoid data on health issues. Data Science J 4, 77–81 (2005)

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  3. Cudek, P., Grzymała-Busse, J.W., Hippe, Z.S.: Asymmetry of digital images describing melanocytic skin lesions. In: Burduk, R., Kurzyński, M., Woźniak, M., Żołnierek, A., et al. (eds.) Computer Recognition Systems 4. AISC, vol. 95, pp. 605–611. Springer, Heidelberg (2011)

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Cudek, P., Grzymała-Busse, J.W., Hippe, Z.S. (2012). Further Research on Automatic Estimation of Asymmetry of Melanocytic Skin Lesions. In: Hippe, Z.S., Kulikowski, J.L., Mroczek, T. (eds) Human – Computer Systems Interaction: Backgrounds and Applications 2. Advances in Intelligent and Soft Computing, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23172-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-23172-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23171-1

  • Online ISBN: 978-3-642-23172-8

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