The integrity of image acquisition is critical for biliopancreatic EUS reporting, significantly affecting the quality of EUS examinations and disease-related decision-making. However, the quality of EUS reports varies among endoscopists. To address this issue, we developed a deep learning–based EUS automatic image report system (EUS-AIRS), aiming to achieve automatic photodocumentation in real-time during EUS, including capturing standard stations, lesions, and puncture procedures.

中文翻译：

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基于深度学习的线性 EUS 实时图像报告系统


图像采集的完整性对于胆胰 EUS 报告至关重要，会显著影响 EUS 检查和疾病相关决策的质量。然而，EUS 报告的质量因内镜医师而异。为了解决这个问题，我们开发了一种基于深度学习的 EUS 自动图像报告系统 （EUS-AIRS），旨在在 EUS 期间实现实时自动照片记录，包括捕获标准站、病灶和穿刺程序。