Format

Send to

Choose Destination
Comput Med Imaging Graph. 2011 Mar;35(2):99-104. doi: 10.1016/j.compmedimag.2010.08.004. Epub 2010 Oct 28.

Colour and contrast enhancement for improved skin lesion segmentation.

Author information

1
Department of Computer Science, Loughborough University, Loughborough, UK. gerald.schaefer@ieee.org

Abstract

Accurate extraction of lesion borders is a critical step in analysing dermoscopic skin lesion images. In this paper, we consider the problems of poor contrast and lack of colour calibration which are often encountered when analysing dermoscopy images. Different illumination or different devices will lead to different image colours of the same lesion and hence to difficulties in the segmentation stage. Similarly, low contrast makes accurate border detection difficult. We present an effective approach to improve the performance of lesion segmentation algorithms through a pre-processing step that enhances colour information and image contrast. We combine this enhancement stage with two different segmentation algorithms. One technique relies on analysis of the image background by iterative measurements of non-lesion pixels, while the other technique utilises co-operative neural networks for edge detection. Extensive experimental evaluation is carried out on a dataset of 100 dermoscopy images with known ground truths obtained from three expert dermatologists. The results show that both techniques are capable of providing good segmentation performance and that the colour enhancement step is indeed crucial as demonstrated by comparison with results obtained from the original RGB images.

[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center