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The Helsinki Rat Microsurgical Sidewall Aneurysm Model
Published on: October 12, 2014
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内动脉瘤CTA图像和3D模型数据集,包括临床形态和血液动力学数据
Miao Song1, Simin Wang1, Qian Qian2
1College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China.
Scientific data
|November 12, 2024
概括
这项研究引入了脑动脉瘤成像和血液动力学数据的新数据集. 本资源旨在促进人工智能研究,以预测动脉瘤破裂风险.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 计算流体动力学的流体动力学.
背景情况:
- 内动脉瘤具有明显的破裂风险,导致严重的后果.
- 目前用于动脉瘤预测的AI研究缺乏足够的公共数据集.
- 医学图像分析对于理解动脉瘤发育至关重要.
研究的目的:
- 为在内动脉瘤研究中开发人工智能模型提供一个全面的数据集.
- 提供形态和血液动力学参数,以帮助没有CFD专业知识的研究人员.
- 为了促进对内动脉瘤的更深入的理解和预测.
主要方法:
- 收集了99名患有MCA动脉瘤的患者和44名健康对照者的高分辨率CTA图像.
- 从CTA数据生成动脉瘤和母动脉的3D模型.
- 包括计算流体动力学 (CFD) 衍生的形态和血液动力学参数.
主要成果:
- 一个数据集105个MCA动脉瘤和44个控制与相关的临床数据.
- 3D模型和CFD参数已集成用于高级分析.
- 该数据集已准备好用于人工智能模型培训和验证.
结论:
- 提出的数据集解决了对动脉瘤研究公共资源的关键需求.
- 它支持对动脉瘤发作,进展和破裂的假设驱动和数据驱动的调查.
- 这种资源有可能大大推进人工智能驱动的脑血管疾病预测.
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