GastroVision

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

本团队荣幸推出GastroVision多中心开放访问性胃肠道（GI）内窥镜数据集，该数据集涵盖多种解剖标志、病理异常、息肉移除病例及胃肠道正常发现。数据集包含来自27个不同类别的8,000张图像，图像采集自挪威的Baerum医院以及瑞典的卡罗琳斯卡大学，并由经验丰富的GI内窥镜医师进行标注和验证。此外，我们通过广泛的基准测试，基于流行的基于深度学习的基线模型，验证了本数据集的重要性。本数据集可促进基于AI的胃肠道疾病检测与分类算法的开发。另可从以下链接下载：https://drive.google.com/drive/folders/1T35gqO7jIKNxC-gVA2YVOMdsL7PSqeAa?usp=sharing

搜集汇总

背景与挑战

背景概述

GastroVision是一个多中心开放访问的胃肠道内窥镜数据集，包含8,000张图像，覆盖27个类别，涵盖解剖标志、病理异常、息肉切除和正常发现。数据来自挪威和瑞典的医院，由专家标注验证，并通过深度学习基准测试验证，旨在支持AI算法在胃肠道疾病检测和分类中的应用。