论文标题
力学知情了食管转运的透视检查
Mechanics Informed Fluoroscopy of Esophageal Transport
论文作者
论文摘要
荧光镜检查是一种评估食管疾病（如adalasia，dydyplasia和gerd）（GERD）等食管疾病的放射学程序。它对吞咽过程进行动态成像，并提供解剖学细节以及关于如何通过食道运输吞咽液的定性思想。在这项工作中，我们提出了一种称为力学知情的荧光检查（Fluoromech）的方法，该方法得出了有关食管功能的患者特异性定量信息。 Fluoromech使用卷积神经网络对荧光镜检查产生的图像序列进行分割，并且分段图像成为一维模型的输入，该模型预测了通过食道运输的流体中的流速和压力分布。我们通过开发荧光素技术参考模型来识别和估计潜在的物理标志物（例如食管壁刚度和活跃的弛豫）来扩展该模型。 Fluoromech需要最少的计算时间，因此可以在临床上诊断食管疾病。
Fluoroscopy is a radiographic procedure for evaluating esophageal disorders such as achalasia, dysphasia and gastroesophageal reflux disease (GERD). It performs dynamic imaging of the swallowing process and provides anatomical detail and a qualitative idea of how well swallowed fluid is transported through the esophagus. In this work, we present a method called mechanics informed fluoroscopy (FluoroMech) that derives patient-specific quantitative information about esophageal function. FluoroMech uses a Convolutional Neural Network to perform segmentation of image sequences generated from the fluoroscopy, and the segmented images become input to a one-dimensional model that predicts the flow rate and pressure distribution in fluid transported through the esophagus. We have extended this model by developing a FluoroMech reference model to identify and estimate potential physiomarkers such as esophageal wall stiffness and active relaxation ahead of the peristaltic wave in the esophageal musculature. FluoroMech requires minimal computational time, and hence can potentially be applied clinically in the diagnosis of esophageal disorders.
