Image Segmentation using Gradient based Histogram Thresholding for Skin Lesion Delineation
Authors
Abstract
Image segmentation is a key stage in medical image processing algorithms and machine learning classifiers where identification of discriminative features are of utmost importance. In the case of skin lesions, most of the existing image segmentation approaches aim at minimising some error metric between computed and groundtruth regions of interest (ROI) defined by medical experts, where ROI delineation is not always considered.This paper proposes an image segmentation method for skin lesion delineation, which expands traditional histogram and clustering-based approaches to achieve the best trade-off between both. The proposed method is capable of providing accurate details of the skin lesion borders, without deviating from the coarser borders of the available ground-truth.