Impact of various color LED flashlights and different lighting source to skin distances on the manual and the computer-aided detection of basal cell carcinoma borders

Skin Res Technol. 2014 Feb;20(1):92-6. doi: 10.1111/srt.12090. Epub 2013 Jul 19.

Abstract

Background/aims: Quantitative analysis based on digital skin image has been proven to be helpful in dermatology. Moreover, the borders of the basal cell carcinoma (BCC) lesions have been challenging borders for the automatic detection methods. In this work, a computer-aided dermatoscopy system was proposed to enhance the clinical detection of BCC lesion borders.

Methods: Fifty cases of BCC were selected and 2000 pictures were taken. The lesion images data were obtained with eight colors of flashlights and in five different lighting source to skin distances (SSDs). Then, the image-processing techniques were used for automatic detection of lesion borders. Further, the dermatologists marked the lesions on the obtained photos.

Results: Considerable differences between the obtained values referring to the photographs that were taken at super blue and aqua green color lighting were observed for most of the BCC borders. It was observed that by changing the SSD, an optimum distance could be found where that the accuracy of the detection reaches to a maximum value.

Conclusion: This study clearly indicates that by changing SSD and lighting color, manual and automatic detection of BCC lesions borders can be enhanced.

Keywords: Basal cell carcinoma; border detection; dermatoscopy; image processing.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Carcinoma, Basal Cell / pathology*
  • Color
  • Colorimetry / instrumentation
  • Colorimetry / methods
  • Dermoscopy / instrumentation*
  • Dermoscopy / methods
  • Equipment Design
  • Equipment Failure Analysis
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted / instrumentation*
  • Image Interpretation, Computer-Assisted / methods
  • Lighting / instrumentation*
  • Lighting / methods
  • Male
  • Pattern Recognition, Automated / methods*
  • Photography / instrumentation
  • Photography / methods
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Skin Neoplasms / pathology*