Segmentation of both Diseased and Healthy Skin from Clinical Photographs in a Primary Care Setting

Deep-learning segmentation for skin lesion images

“…We also evaluated a number of recent techniques, focusing on the U-net architecture (RONNEBERGER et al, 2015), which is widely used for biomedical and other small, specific datasets. Our results reinforce the findings of Codella et al (2017) that adding fully-connected layers to the U-net network (which in its original form, only contains convolutional layers) results in better performance. We also found that using a loss based on the Jaccard metric leads to better results, a similar finding to that of in the same ISIC 2017 Challenge.…”

“…The ISBI Challenge (CODELLA et al, 2017) has the goal of helping participants develop image analysis tools to enable the automated diagnosis of melanoma from dermoscopic images. The challenge has three parts, the first of which is lesion segmentation.…”