PFUS1:第一层骨盆地超声波细分数据集. 一个促进研究进步的资源
David Solís-Martín1, José Antonio Sainz2, Juan Galán-Páez1
1Department of Computer Science and Artificial Intelligence, Seville University, Seville, Spain.
Data in brief
|January 6, 2026
概括
这项研究引入了第一个关于盆地解剖学的注释超声波视频数据集,有助于自动化评估和医学图像分析的研究. 该数据集支持计算机辅助诊断和动态器官跟踪方面的进展.
科学领域:
- 医疗成像医学成像
- 计算机视觉 计算机视觉
- 人体解剖学 解剖学 解剖学
背景情况:
- 盆地疾病影响了许多人,需要准确的诊断工具.
- 目前用于骨盆地评估的超声波方法缺乏用于研究的标准化注释数据集.
- 盆地超声视频的自动分析可以提高诊断效率和准确性.
研究的目的:
- 为了呈现一个新的,精心策划的跨骨盆地超声波视频数据集.
- 为八个关键的解剖结构提供像素级的注释.
- 促进自动骨盆底评估,医学图像细分和动态器官跟踪方面的研究.
主要方法:
- 从使用Canon Aplio® i700系统的111名患者收集了经骨盆地超声波视频.
- 在休息和瓦尔萨尔瓦演习期间捕捉到的中腰部视图.
- 专家超声波专家使用CVAT平台手动注释了八个解剖结构,生成了细分面具.
主要成果:
- 现在可以获得一个关于有注释的骨盆地超声视频的全面数据集.
- 为八个盆底解剖结构创建了像素级别的细分面具.
- 公共可用的源代码包括用于数据加载,面具生成和基线深度学习模型培训 (例如,FPN) 的脚本.
结论:
- 这一数据集是第一个关于盆底解剖学的注释超声波视频资源.
- 它使得在计算机辅助诊断和医学图像分析方面实现了基准测试,可重复性和创新.
- 促进了先进的自动化盆底评估工具的开发.
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