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迈向食管动力的多模态可视化:测压、阻抗和视频荧光图像序列的融合。

Towards multimodal visualization of esophageal motility: fusion of manometry, impedance, and videofluoroscopic image sequences.

作者信息

Geiger Alexander, Bernhard Lukas, Gassert Florian, Feußner Hubertus, Wilhelm Dirk, Friess Helmut, Jell Alissa

机构信息

Technical University of Munich, TUM School of Medicine and Health, Klinikum rechts der Isar, Research Group MITI, Munich, Germany.

Technical University of Munich, TUM School of Medicine and Health, Klinikum rechts der Isar, Department of Radiology, Munich, Germany.

出版信息

Int J Comput Assist Radiol Surg. 2025 Apr;20(4):713-721. doi: 10.1007/s11548-024-03265-1. Epub 2024 Oct 8.

Abstract

PURPOSE

Dysphagia is the inability or difficulty to swallow normally. Standard procedures for diagnosing the exact disease are, among others, X-ray videofluoroscopy, manometry and impedance examinations, usually performed consecutively. In order to gain more insights, ongoing research is aiming to collect these different modalities at the same time, with the goal to present them in a joint visualization. One idea to create a combined view is the projection of the manometry and impedance values onto the right location in the X-ray images. This requires to identify the exact sensor locations in the images.

METHODS

This work gives an overview of the challenges associated with the sensor detection task and proposes a robust approach to detect the sensors in X-ray image sequences, ultimately allowing to project the manometry and impedance values onto the right location in the images.

RESULTS

The developed sensor detection approach is evaluated on a total of 14 sequences from different patients, achieving a F1-score of 86.36%. To demonstrate the robustness of the approach, another study is performed by adding different levels of noise to the images, with the performance of our sensor detection method only slightly decreasing in these scenarios. This robust sensor detection provides the basis to accurately project manometry and impedance values onto the images, allowing to create a multimodal visualization of the swallow process. The resulting visualizations are evaluated qualitatively by domain experts, indicating a great benefit of this proposed fused visualization approach.

CONCLUSION

Using our preprocessing and sensor detection method, we show that the sensor detection task can be successfully approached with high accuracy. This allows to create a novel, multimodal visualization of esophageal motility, helping to provide more insights into swallow disorders of patients.

摘要

目的

吞咽困难是指无法正常吞咽或吞咽困难。诊断确切疾病的标准程序包括X线电视透视检查、测压和阻抗检查等,通常是依次进行。为了获得更多见解,正在进行的研究旨在同时收集这些不同的检查方式,目标是以联合可视化的形式呈现它们。创建组合视图的一个想法是将测压和阻抗值投影到X线图像的正确位置上。这需要识别图像中传感器的确切位置。

方法

本文概述了与传感器检测任务相关的挑战,并提出了一种稳健的方法来检测X线图像序列中的传感器,最终能够将测压和阻抗值投影到图像的正确位置上。

结果

所开发的传感器检测方法在来自不同患者的总共14个序列上进行了评估,F1分数达到86.36%。为了证明该方法的稳健性,通过向图像中添加不同程度的噪声进行了另一项研究,在这些情况下我们的传感器检测方法的性能仅略有下降。这种稳健的传感器检测为将测压和阻抗值准确投影到图像上提供了基础,从而能够创建吞咽过程的多模态可视化。领域专家对所得的可视化结果进行了定性评估,表明这种提出的融合可视化方法有很大益处。

结论

使用我们的预处理和传感器检测方法,我们表明传感器检测任务可以高精度地成功完成。这使得能够创建一种新颖的食管动力多模态可视化,有助于更深入了解患者的吞咽障碍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f260/12034594/8e2e6642e698/11548_2024_3265_Fig1_HTML.jpg

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