Localization of cutaneous lesions in digital images

Digital imaging could potentially provide a rapid, objective, and quantitative means of detecting changes in important skin conditions, especially the dysplasic nevus syndrome. Image analysis techniques can be applied to digital images to automate the search for changes in moles or other features. Consistent determination of lesion boundaries, perimeter, and area in digital images is a vital first step in this process. In this paper, we show how bilaterally symmetric Laplacian-of-a-Gaussian filters can be used to recover the borders of selected lesions while remaining robust with respect to factors such as the camera point spread function and additive noise. Tests on real and synthetic images demonstrate that lesion borders, area, and perimeter can be obtained with a high degree of reliability. Boundaries are routinely found to within +/- 0.2 pixels, and area and perimeter measurements vary by less than 10% when imaging spot targets and actual cutaneous lesions under a realistic range of experimental conditions.