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Category: Data

Description: Artificial intelligence is currently a hot topic in medicine. The fact that medical data is often sparse for various reasons leads to technical limitations. In this respect, we share the HyperKvasir dataset, which is the largest multi-class image and video dataset from the gastrointestinal tract available today. The data is collected during real gastro- and colonoscopy examinations at a Hospital in Norway and partly labeled by experienced gastrointestinal endoscopists. The dataset contains 110,079 images and 374 videos where it captures anatomical landmarks and pathological and normal findings giving in total around 1 million images and video frames. A zip of the complete dataset can be downloaded at https://datasets.simula.no/hyper-kvasir The paper describing the dataset (which should be cited when the dataset is used), is found here: https://doi.org/10.1038/s41597-020-00622-y Additional data created by the experiments and source code can be found in this Github repository: https://github.com/simula/hyper-kvasir