ERCPMP:一个内镜图像和视频数据集,用于结直肠息肉的形态和病理
Mojgan Forootan1, Mohsen Rajabnia2, Ahmad R Mafi1
1Gastroenterology and Liver Disease Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
BMC research notes
|December 28, 2024
概括
这一数据集为开发人工智能算法提供了有价值的结直肠多的内镜图像和视频. 它有助于检测,分类和细分的息肉,提高诊断的准确性.
科学领域:
- 胃肠病学 胃肠病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 准确的医疗预测,诊断和预后算法是关键的挑战.
- 高质量的数据集对于在医疗保健中开发强大的深度学习模型至关重要.
研究的目的:
- 引入内镜图像和视频数据集,用于识别结肠直肠息肉的形状和病理 (ERCPMP).
- 为培训和验证结直肠多分析深度学习算法提供全面的数据集.
主要方法:
- 该数据集包括来自191名结直肠多瘤患者的人口统计,形态和病理数据.
- 内镜图像和视频是使用奥林巴斯大肠镜拍摄的,以RGB JPG格式 (368x256像素,96dpi) 呈现.
- 形态学数据遵循国际分类 (巴黎,Pit,JNET);病理学数据包括多的诊断和等级.
主要成果:
- 数据集包括详细的病理诊断,如管状,状,管状,超塑性,状,炎症性和带有失塑性等级和差异化的腺癌.
- 文件命名规范整合了病理诊断,等级和JNet分类,以便轻松检索和分析数据.
结论:
- ERCPMP数据集是推进自动化结直肠多检测,分类和细分研究的宝贵资源.
- 这一数据集有助于在胃肠病学中开发基于深度学习的改进诊断工具.
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