Quantitative color analysis for capillaroscopy image segmentation

Michela Goffredo, Maurizio Schmid, Silvia Conforto, Beatrice Amorosi, Tommaso D'Alessio, Claudio Palma

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)567-574
Number of pages8
JournalMedical and Biological Engineering and Computing
Volume50
Issue number6
DOIs
Publication statusPublished - Jun 2012

Keywords

  • Capillaroscopy
  • Color analysis
  • Color space
  • Segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications
  • Medicine(all)

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