Quantitative color analysis for capillaroscopy image segmentation.

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 dermatolog...

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Publicado en:Medical & Biological Engineering & Computing Vol. 50; no. 6; pp. 567 - 575
Autores principales: Goffredo M, Schmid M, Conforto S, Amorosi B, D'Alessio T, Palma C, Goffredo, Michela, Schmid, Maurizio, Conforto, Silvia, Amorosi, Beatrice, D'Alessio, Tommaso, Palma, Claudio
Formato: research Journal Article
Publicado: Springer Nature Jun2012
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2012
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      pub: Springer Nature
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        atl: Quantitative color analysis for capillaroscopy image segmentation.
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        au:
          Goffredo M
          Schmid M
          Conforto S
          Amorosi B
          D'Alessio T
          Palma C
          Goffredo, Michela
          Schmid, Maurizio
          Conforto, Silvia
          Amorosi, Beatrice
          D'Alessio, Tommaso
          Palma, Claudio
        affil: Department of Applied Electronics, University "Roma TRE", Rome, Italy
      sug:
        subj:
          Image Interpretation, Computer Assisted Methods
          Angioscopy Methods
          Nails Blood Supply
          Algorithms
          Capillaries Pathology
          Color
          Human
      ab: 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.
      pubtype: Academic Journal
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        research
        Journal Article
      ougenre: Article
    language: English
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