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Computerised image analysis of vitiligo lesion: evaluation using manually defined lesion areas. | LitMetric

Computerised image analysis of vitiligo lesion: evaluation using manually defined lesion areas.

Skin Res Technol

Intelligent Signal and Imaging Research Centre, Department of Electrical & Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia.

Published: February 2013

AI Article Synopsis

  • Vitiligo is a skin disorder marked by loss of pigment, typically assessed subjectively by physicians through the physician's global assessment (PGA) method.
  • A new digital image processing technique uses Independent Component Analysis (ICA) and Region Growing to objectively measure the area of vitiligo lesions.
  • Testing on 41 images from 18 patients demonstrated high sensitivity (91.05%), specificity (99.73%), and accuracy (99.01%), allowing for more accurate assessments of treatment efficacy.

Article Abstract

Background: Vitiligo is a cutaneous pigmentary disorder characterized by depigmented macules and patches that result from loss of epidermal melanocytes. Physician evaluates the efficacy of treatment by comparing the extent of vitiligo lesions before and after treatment based on the overall visual impression of the treatment response. This method is called the physician's global assessment (PGA) which is subjective. In this article, we present an innovative digital image processing method to determine vitiligo lesion area in an objective manner.

Method: The digital method uses Independent Component Analysis (ICA) to generate melanin-based images representing skin areas due to melanin followed by Region Growing process to segment vitiligo lesion from normal skin.

Results: Based on 41 digital images of vitiligo lesions taken from 18 patients, the proposed method achieved sensitivities of 0.9105 ± 0.0161, specificities of 0.9973 ± 0.0009 and accuracies of 0.9901 ± 0.0028 at 95% confidence level.

Conclusion: With the proposed method, physicians are able to assess vitiligo treatment efficacies objectively.

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Source
http://dx.doi.org/10.1111/j.1600-0846.2011.00610.xDOI Listing

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