This work considers electrical impedance tomography imaging of the human head, with the ultimate goal of locating and classifying a stroke in emergency care. One of the main difficulties in the envisioned application is that the electrode locations and the shape of the head are not precisely known, leading to significant imaging artifacts due to impedance tomography being sensitive to modeling errors. In this study, the natural variations in the geometry of the head and skull are modeled based on a library of head anatomies. The effect of these variations, as well as that of misplaced electrodes, on (absolute) impedance tomography measurements is in turn modeled by the approximation error method. This enables reliably reconstructing the conductivity perturbation caused by the stroke in an average head model, instead of the actual head, relative to its average conductivity levels. The functionality of a certain edge-preferring reconstruction algorithm for locating the stroke is demonstrated via numerical experiments based on simulated three-dimensional data.

翻译：这项工作考虑了人体头部阻碍电阻断层摄影成像,最终目标是在紧急护理中定位和分类中中风。设想应用中的一个主要困难是,电极位置和头形的形状并不确切为人所知,导致大量成像文物,因为阻断断断层成像对建模错误十分敏感。在这项研究中,头部和头骨几何的自然变异以头部解剖图书馆为模型模型。这些变异以及错位电极对(绝对)阻碍造影测量的影响由近似误差法制成。这可以可靠地重建平均头型中风而不是实际头部与平均导电率水平相比造成的导振动。根据模拟三维数据进行的数字实验可以证明中风定位的某些边缘预测重建算法的功能。