在视频光镜吞研究中用于吞检测的多式框架,该研究使用了失症患者的尺度压力分布
Manuel Maria Loureiro da Rocha1,2, Lisette van der Molen3, Marise Neijman3
1Robotics and Mechatronics Group, University of Twente, Drienerlolaan 5, Enschede, 7522 NB, the Netherlands. m.m.rocha@utwente.nl.
International journal of computer assisted radiology and surgery
|December 16, 2025
概括
一个新的自动化框架使用视频光学吞研究 (VFSS) 和高分辨率阻抗计量 (HRIM) 准确检测头癌患者的吞. 这将使临床医生的工作量减少63%,同时保持高准确度.
科学领域:
- 生物医学工程 生物医学工程
- 临床诊断 临床诊断 临床诊断
- 吞障碍 吞障碍 吞障碍
背景情况:
- 口腔喉功能障碍在头癌 (HNC) 患者中很常见,影响高达50%的患者.
- 综合的吞评估通常涉及同时进行视频光学吞研究 (VFSS) 和高分辨率阻抗力计 (HRIM).
- 由于高临床工作量和复杂的数据分析,目前的方法面临挑战.
研究的目的:
- 开发一个自动化框架,用于同时对HNC患者进行VFSS-HRIM检查的吞检测.
- 解决临床数据收集和分析现有软件的局限性.
- 为了减少临床医生的工作量,同时保持高精度的吞评估.
主要方法:
- 建议使用VFSS视频和HRIM数据进行自动吞检测的框架.
- 采用优化的双扫光流算法来识别候选吞间隔.
- 使用基于压力的吞模板,使用来自上食道关节传感器的特征进行分类.
主要成果:
- 在12名HNC患者的97次吞中进行了评估.
- 实现了95%的回忆和92%的F1分数,用于吞检测.
- 将HRIM注释的需求减少了63%,显著降低了临床医生的工作量.
结论:
- 开发的框架可以在接受VFSS-HRIM的HNC患者中准确,低输入的吞检测.
- 它克服了当前软件的局限性,促进了可扩展,客观和多式联运的吞评估.
- 这项技术为改善与HNC相关的食障碍的诊断能力奠定了基础.
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