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Spatial-dependent regularization to solve the inverse problem in electromyometrial imaging.
Medical & Biological Engineering & Computing ( IF 3.2 ) Pub Date : 2020-05-26 , DOI: 10.1007/s11517-020-02183-z
Hui Wang 1, 2, 3 , Yong Wang 2, 3, 4, 5
Affiliation  

Recently, electromyometrial imaging (EMMI) was developed to non-invasively image uterine contractions in three dimensions. EMMI collects body surface electromyography (EMG) measurements and uses patient-specific body-uterus geometry generated from magnetic resonance images to reconstruct uterine electrical activity. Currently, EMMI uses the zero-order Tikhonov method with mean composite residual and smoothing operator (CRESO) to stabilize the underlying ill-posed inverse computation. However, this method is empirical and implements a global regularization parameter over all uterine sites, which is sub-optimal for EMMI given the severe eccentricity of body-uterus geometry. To address this limitation, we developed a spatial-dependent (SP) regularization method that considers both body-uterus eccentricity and EMG noise. We used electrical signals simulated with spherical and realistic geometry models to compare the reconstruction accuracy of the SP method to those of the CRESO and the L-Curve methods. The SP method reconstructed electrograms and potential maps more accurately than the other methods, especially in cases of high eccentricity and noise contamination. Thus, the SP method should facilitate clinical use of EMMI and can be used to improve the accuracy of other electrical imaging modalities, such as Electrocardiographic Imaging.

The spatial-dependent regularization (SP) technique was designed to improve the accuracy of Electromyometrial Imaging (EMMI). The top panel shows the eccentricity of body-uterus geometry and four representative body surface electrograms. The bottom panel shows boxplots of correlation coefficients and relative errors for the electrograms reconstructed with SP and two conventional methods, the L-Curve and mean CRESO methods.



中文翻译:

解决肌电成像逆问题的空间相关正则化。

最近,肌电成像 (EMMI) 被开发用于在三个维度上对子宫收缩进行非侵入性成像。EMMI 收集体表肌电图 (EMG) 测量值,并使用从磁共振图像生成的特定于患者的身体 - 子宫几何结构来重建子宫电活动。目前,EMMI 使用具有平均复合残差和平滑算子 (CRESO) 的零阶 Tikhonov 方法来稳定底层病态逆计算。然而,这种方法是经验性的,并且在所有子宫部位上实现了全局正则化参数,鉴于身体 - 子宫几何形状的严重偏心,这对于 EMMI 来说是次优的。为了解决这个限制,我们开发了一种空间相关 (SP) 正则化方法,它同时考虑了身体 - 子宫离心率和 EMG 噪声。我们使用球形和真实几何模型模拟的电信号来比较 SP 方法与 CRESO 和 L 曲线方法的重建精度。SP 方法比其他方法更准确地重建电图和电位图,尤其是在高偏心和噪声污染的情况下。因此,SP 方法应促进 EMMI 的临床使用,并可用于提高其他电成像模式的准确性,例如心电图成像。

空间相关正则化 (SP) 技术旨在提高肌电成像 (EMMI) 的准确性。顶部面板显示了身体 - 子宫几何形状的偏心率和四个代表性的体表电图。底部面板显示了使用 SP 和两种传统方法(L 曲线和平均 CRESO 方法)重建的电图的相关系数和相对误差的箱线图。

更新日期:2020-05-26
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