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Quantitative color analysis for capillaroscopy image segmentation

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Abstract

This communication introduces a novel approach for quantitatively evaluating the role of color space decomposition in digital nailfold capillaroscopy analysis. It is clinically recognized that any alterations of the capillary pattern, at the periungual skin region, are directly related to dermatologic and rheumatic diseases. The proposed algorithm for the segmentation of digital capillaroscopy images is optimized with respect to the choice of the color space and the contrast variation. Since the color space is a critical factor for segmenting low-contrast images, an exhaustive comparison between different color channels is conducted and a novel color channel combination is presented. Results from images of 15 healthy subjects are compared with annotated data, i.e. selected images approved by clinicians. By comparison, a set of figures of merit, which highlights the algorithm capability to correctly segment capillaries, their shape and their number, is extracted. Experimental tests depict that the optimized procedure for capillaries segmentation, based on a novel color channel combination, presents values of average accuracy higher than 0.8, and extracts capillaries whose shape and granularity are acceptable. The obtained results are particularly encouraging for future developments on the classification of capillary patterns with respect to dermatologic and rheumatic diseases.

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Acknowledgments

We gratefully acknowledge the support of IFO San Gallicano Dermatology Institute, IRCCS, Rome, Italy. In particular, we thank A. Di Carlo and M. Ardigò for the time patiently spent with us.

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Authors and Affiliations

  1. Department of Applied Electronics, University “Roma TRE”, Rome, Italy

    Michela Goffredo, Maurizio Schmid, Silvia Conforto & Tommaso D’Alessio

  2. IFO San Gallicano Dermatology Institute, IRCCS, Rome, Italy

    Beatrice Amorosi

  3. Department of Physics, University “Roma TRE”, Rome, Italy

    Claudio Palma

Authors
  1. Michela Goffredo
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  2. Maurizio Schmid
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  3. Silvia Conforto
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  4. Beatrice Amorosi
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  5. Tommaso D’Alessio
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  6. Claudio Palma
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Correspondence to Michela Goffredo.

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Goffredo, M., Schmid, M., Conforto, S. et al. Quantitative color analysis for capillaroscopy image segmentation. Med Biol Eng Comput 50, 567–574 (2012). https://doi.org/10.1007/s11517-012-0907-7

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  • DOI: https://doi.org/10.1007/s11517-012-0907-7

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