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从半监督的深度特征提取中进行可调和和实时的自动干预X射线对接.

Brian C Lee¹, Damini Rijhwani¹, Sydney Lang¹

¹Philips Research, Cambridge, Massachusetts, USA.

Medical physics

|December 6, 2024

概括

用于干预性X射线手术的自动化聚合算法显著减少了患者和工作人员的辐射暴露. 这种可调节的系统可以无地集成到工作流程中,保持程序质量和时间,同时提高安全性.

关键词:

结合聚合 (collimation) 是一种方法.内血管外科手术是一种内血管手术.干预性放射学是干预性的放射学.一个X射线.

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科学领域:

医疗成像医学成像
干预性放射学干预性放射学
健康物理物理

背景情况:

内血管程序越来越常见,依靠c-arm X射线系统进行图像指导.
在这些程序期间的光镜对患者和工作人员构成辐射风险,工作流程的修改可能会影响程序时间或质量.
由于手工复杂性和不同的干预主义者偏好,当前的合并实践未得到充分利用.

研究的目的:

开发和评估一个自动化的对接系统,以提高图像质量和减少干预性X射线手术中的辐射暴露.
解决手动配合的挑战,包括其繁的性质和程序期间参数操纵的困难.
创建一个系统,以适应不同程序和不同解剖学的不同协同偏好.

主要方法:

提出了一种可调节的算法,用于使用兴趣区域优化器进行自动对接.
将图像,系统,设备和辐射功能集成到算法中.
开发了一种在算法参数和实际结果之间有明确映射的方法,通过卷积神经网络实现了深度特征提取.

主要成果:

在模拟和临床辐射访问程序数据集上展示实时实施和评估性能.
展示了减少辐射的潜力,并评估了混合监督培训战略的影响.
与专家放射科医生进行的读者研究证实了100%的临床可接受性,高质量评级和改进的辐射保护.

结论:

自动对接算法的模块化设计满足了用户的要求,而不会破坏工作流程或程序时间.
该系统显示出降低患者和操作人员辐射风险的巨大潜力.
建议在不同的临床环境中进行进一步的评估,以支持临床转化.