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BraTioUS: 一个多中心数据集的基线手术内脑瘤超声波图像
Olga Esteban-Sinovas1,2, Rosario Sarabia1,2, Ignacio Arrese1,2
1Department of Neurosurgery, Río Hortega University Hospital, Valladolid 47014, Spain.
Data in brief
|February 9, 2026
概括
布拉蒂奥斯数据集提供了大量用于脑瘤手术的手术内超声波图像. 本资源有助于训练人工智能模型,以提高质瘤手术的解释和患者的治疗结果.
科学领域:
- 神经外科 神经外科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 术内超声波 (ioUS) 对于质瘤手术至关重要.
- 现有的数据集在硬件,协议和质瘤类型方面缺乏多样性.
- 人工智能开发需要大规模,异质的ioUS数据.
研究的目的:
- 介绍BraTioUS数据集,一个全面的ioUS图像集合.
- 为ioUS解释提供培训和验证机器学习模型的资源.
- 解决现有数据集的局限性,并在神经外科手术中推进AI.
主要方法:
- 在六家国际医院收集了来自142名质瘤患者的1669张B模式二维IOUS图像.
- 图像采集于2018-2023年间,使用多种超声波系统和协议.
- 包括专家监督的瘤细分面具,用于每张IOUS图像.
主要成果:
- 建立了BraTioUS作为最大的公开可用的多中心ioUS数据集,用于质瘤手术.
- 数据集在获取硬件,协议和质瘤类型方面表现出显著的异质性.
- 提供高质量的,专家注释的数据,适合人工智能模型开发.
结论:
- BraTioUS是一个有价值的,多样化的资源,用于推进人工智能在手术中的超声波用于质瘤手术.
- 该数据集有助于开发改进的AI工具,用于手术决策.
- 通过在手术期间更好地解释IOUS,促进了改善患者的治疗结果.
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