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GastroVision
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Description: We present GastroVision, a multi-center open-access gastrointestinal (GI) endoscopy dataset that includes different anatomical landmarks, pathological abnormalities, polyp removal cases, and normal findings from the GI tract. The dataset comprised 8,000 images from 27 different classes and was acquired from Baerum Hospital in Norway and Karolinska University in Sweden and was annotated and verified by experienced GI endoscopists. Furthermore, we validate the significance of our dataset with extensive benchmarking based on the popular deep learning based baseline models. Our dataset can facilitate the development of AI-based algorithms for GI disease detection and classification. Alternatively, the dataset can be also downloaded from https://drive.google.com/drive/folders/1T35gqO7jIKNxC-gVA2YVOMdsL7PSqeAa?usp=sharing
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection
[Preprint]
We present an open-access multi-class GI endoscopy dataset, namely, Gastrovision, containing 8,000 images with 27 classes from two hospitals in Norway and Sweden. The dataset exhibits a diverse range of classes, including anatomical landmarks, pathological findings, polyp removal c…
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