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International Conference on Intelligent Computing

ICIC 2017: Intelligent Computing Theories and Application pp 35–44Cite as

Leg Ulcer Long Term Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10362))

Abstract

Ulcers on legs and feet usually require long-term clinical treatment and follow-up. To facilitate the monitoring, we propose a fully automatic and low-cost method for ulcers detection and analysis. The ulcer segmentation is performed using an automatic processing based on pixel’s classification into background or not background classes. Features used to perform the classification are the values of three channels that define each pixel in the RGB color map and in the HSV color map.

We tested the algorithm on a dataset of 92 images, acquired from 14 different patients. The segmentation performances were evaluated in terms of overlap, recall and precision, by comparing the automatic segmentation with the manually one. The results show good average values of overlap, recall and precision.

Then, a Self-Organizing Map (SOM) was used for tissue classification. The SOM was trained in order to identify six colorimetric classes associated to different type of tissues.

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Acknowledgment

This project was partly funded by Italian MIUR OPLON project.

Authors would like to thank Dr. Franco Ribero for his precious help and the ulcer images.

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Authors and Affiliations

  1. DET, Politecnico di Torino, c. Duca d. Abruzzi 24, 10129, Turin, Italy

    Eros Pasero & Cristina Castagneri

Authors
  1. Eros Pasero
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  2. Cristina Castagneri
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Corresponding author

Correspondence to Eros Pasero .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

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Pasero, E., Castagneri, C. (2017). Leg Ulcer Long Term Analysis. In: Huang, DS., Jo, KH., Figueroa-García, J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10362. Springer, Cham. https://doi.org/10.1007/978-3-319-63312-1_4

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  • DOI: https://doi.org/10.1007/978-3-319-63312-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63311-4

  • Online ISBN: 978-3-319-63312-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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