Skin Lesion Segmentation

Lesion segmentation data includes the original image, paired with the expert manual tracing of the lesion boundaries in the form of a binary mask. The Training Data file is a ZIP file, containing 900 dermoscopic lesion images in JPEG format. All images are named using the scheme ISIC_<image_id>.jpg, where <image_id> is a 7-digit unique identifier. EXIF tags in the images have been removed; any remaining EXIF tags should not be relied upon to provide accurate metadata. The Training Ground Truth file is a ZIP file, containing 900 binary mask images in PNG format. All masks are named using the scheme ISIC_<image_id>_Segmentation.png, where <image_id> matches the corresponding Training Data image for the mask. All mask images will have the exact same dimensions as their corresponding lesion image. Mask images are encoded as single-channel (grayscale) 8-bit PNGs (to provide lossless compression), where each pixel is either: 0: representing the background of the image or areas outside the lesion 255: representing the foreground of the image or areas inside the lesion

The dataset is maintained by VISION AND IMAGE PROCESSING LAB, University of Waterloo. The images of the dataset were extracted from the public databases DermIS and DermQuest, along with manual segmentations of the lesions. The dataset was used in the following journal publication. [1] Glaister, J., A. Wong, and D. A. Clausi, "Automatic segmentation of skin lesions from dermatological photographs using a joint probabilistic texture distinctiveness approach", IEEE Transactions on Biomedical Engineering [2] Amelard, R., J. Glaister, A. Wong, and D. A. Clausi, "High-level intuitive features (HLIFs) for intuitive skin lesion descriptionpdf", IEEE Transactions on Biomedical Engineering, vol. 62, issue 3, pp. 820-831, October, 2015. [3] Glaister, J., R. Amelard, A. Wong, and D. A. Clausi, "MSIM: Multi-Stage Illumination Modeling of Dermatological Photographs for Illumination-Corrected Skin Lesion Analysis", IEEE Transactions on Biomedical Engineering, vol. 60, issue 7, pp. 1873 - 1883, November, 2013.