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CT 图像引导电阻抗断层成像在医学成像中的应用。

CT Image-Guided Electrical Impedance Tomography for Medical Imaging.

出版信息

IEEE Trans Med Imaging. 2020 Jun;39(6):1822-1832. doi: 10.1109/TMI.2019.2958670. Epub 2019 Dec 10.

DOI:10.1109/TMI.2019.2958670
PMID:31831409
Abstract

This study presents a computed tomography (CT) image-guided electrical impedance tomography (EIT) method for medical imaging. CT is a robust imaging modality for accurately reconstructing the density structure of the region being scanned. EIT can detect electrical impedance abnormalities to which CT scans may be insensitive, but the poor spatial resolution of EIT is a major concern for medical applications. A cross-gradient method has been introduced for oil and gas exploration to jointly invert multiple geophysical datasets associated with different medium properties in the same geological structure. In this study, we develop a CT image-guided EIT (CEIT) based on the cross-gradient method. We assume that both CT scanning and EIT imaging are conducted for the same medical target. A CT scan is first acquired to help solve the subsequent EIT imaging problem. During EIT imaging, we apply cross gradients between the CT image and the electrical conductivity distribution to iteratively constrain the conductivity inversion. The cross-gradient based method allows the mutual structures of different physical models to be referenced without directly affecting the polarity and amplitude of each model during the inversion. We apply the CEIT method to both numerical simulations and phantom experiments. The effectiveness of CEIT is demonstrated in comparison with conventional EIT. The comparison shows that the CEIT method can significantly improve the quality of conductivity images.

摘要

本研究提出了一种基于计算机断层扫描(CT)图像引导的电阻抗断层成像(EIT)方法,用于医学成像。CT 是一种强大的成像方式,可以准确重建被扫描区域的密度结构。EIT 可以检测到 CT 扫描可能不敏感的电导率异常,但 EIT 的空间分辨率差是医学应用中的一个主要关注点。交叉梯度方法已被引入用于石油和天然气勘探,以联合反演与同一地质结构中不同介质特性相关的多个地球物理数据集。在本研究中,我们开发了一种基于交叉梯度方法的 CT 图像引导 EIT(CEIT)。我们假设 CT 扫描和 EIT 成像都是针对相同的医学目标进行的。首先进行 CT 扫描,以帮助解决随后的 EIT 成像问题。在 EIT 成像过程中,我们应用 CT 图像和电导率分布之间的交叉梯度来迭代地约束电导率反演。基于交叉梯度的方法允许参考不同物理模型的相互结构,而在反演过程中不会直接影响每个模型的极性和幅度。我们将 CEIT 方法应用于数值模拟和体模实验。CEIT 的有效性通过与传统 EIT 的比较得到了证明。比较结果表明,CEIT 方法可以显著提高电导率图像的质量。

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