Dermoscopic Dataset from the International Skin Imaging Collaboration (ISIC) Project

The dermoscopic images considered in the paper"Dermoscopic Image Classification with Neural Style Transfer"are available for public download through the ISIC database (https://www.isic-archive.com/#!/topWithHeader/wideContentTop/main). These are 24-bit JPEG images with a typical resolution of 768 × 512 pixels. However, not all the images in the database are in satisfactory condition. Therefore, we constructed a high-quality, balanced dataset of 1000 images (500 malignant and 500 benign) by omitting the images that satisfy any of the following conditions: (a) the entirety of the tumor does not fit within the image frame, (b) an abundance of hair which blocks a significant portion of the lesion, (c) are duplicated or augmented versions of other images. This data cleaning is necessary in order to ensure accurate border detection, reliable feature extraction, a fair comparison of classification performances, and satisfactory quality control for the style-transferred images without the interference of non-lesion information. The images are resized to 224 x 224 pixels using bilinear interpolation to reduce the computation cost of our analysis. The lesion segmentation mask for each image, trained using U-net on the PH2 dataset (https://www.fc.up.pt/addi/ph2 database.html) is also provided.This paper also considered both the ISIC 2016 and ISIC 2017 competitions on skin lesion classification. They are both available for download at https://challenge.isic-archive.com/data.