基于噪声的电阻抗断层成像校正方法
Noise-based Correction for Electrical Impedance Tomography
AI总结：
针对电阻抗断层成像中测量噪声导致图像质量差的问题，提出基于噪声的校正后处理方法，经模拟、物理实验及在体验证，该方法可稳定提升图像质量，推荐采用非相关噪声版本作为通用技术。
摘要：
研究背景与问题：在电阻抗成像中，含噪测量值常会生成噪声大、精度低的图像，目前尚无后处理技术可计算测量噪声的传播规律并利用该规律抑制图像噪声。研究目标：本工作的目标包括：（1）开发一种用于电阻抗断层成像的基于噪声的校正（noise-based correction，NBC）后处理方法；（2）测试NBC是否能提升电阻抗断层成像（electrical impedance tomography，EIT）的图像质量；（3）确定NBC采用相关噪声还是非相关噪声效果更优；（4）测试NBC是否适用于在体数据；（5）测试NBC在不同模型和扰动几何结构下是否稳定。研究方法：在二维均匀圆形域和解剖结构真实的异质三维人类头部域中开展计算机模拟EIT实验，每种场景设置4种扰动和25个噪声水平。通过在二维圆形盐水槽、带真实颅骨样层的三维人头形盐水槽中开展4种扰动的EIT实验进行验证。采用相对于目标图像的加权空间方差（weighted spatial variance，WSV）评估图像质量，同时在人类胸部肺通气、大鼠大脑皮层活动的在体EIT示例数据上测试NBC的效果。研究结果：目视观察显示，在二维和三维的模拟及实验场景中，NBC在所有扰动和噪声水平下均能保持或提升图像质量。WSV分析表明，NBC在几乎所有场景下都能显著改善WSV指标；当NBC处理后的WSV更差时，这种差异要么目视无法察觉，要么只是含噪图像间的转换。对于在体数据，NBC在所有案例中均提升了图像质量，且保留了重建扰动的预期形状。实际应用中，非相关NBC的表现优于相关NBC，推荐作为EIT的通用后处理技术。
英文摘要：
Introduction. Noisy measurements frequently cause noisy and inaccurate images in impedance imaging. No post-processing technique exists to calculate the propagation of measurement noise and use this to suppress noise in the image. Objectives. The objectives of this work were (1) to develop a post-processing method for noise-based correction (NBC) in impedance tomography, (2) to test whether NBC improves image quality in electrical impedance tomography (EIT), (3) to determine whether it is preferable to use correlated or uncorrelated noise for NBC, (4) to test whether NBC works with in vivo data and (5) to test whether NBC is stable across model and perturbation geometries. Methods. EIT was performed in silico in a 2D homogeneous circular domain and an anatomically realistic, heterogeneous 3D human head domain for four perturbations and 25 noise levels in each case. This was validated by performing EIT for four perturbations in a circular, saline tank in 2D as well as a human head-shaped saline tank with a realistic skull-like layer in 3D. Images were assessed on the weighted spatial variance (WSV) with respect to the target image. The effect of NBC was also tested for example in vivo EIT data of lung ventilation in a human thorax and cortical activity in a rat brain. Results. On visual inspection, NBC maintained or increased image quality for all perturbations and noise levels in 2D and 3D experimentally and in silico. Analysis of the WSV showed that NBC significantly improved the WSV in nearly all cases. When the WSV was inferior with NBC, this was either visually imperceptible or a transformation between noisy images. For in vivo data, NBC improved image quality in all cases and preserved the expected shape of the reconstructed perturbation. In practice, uncorrelated NBC performed better than correlated NBC and is recommended as a general-use post-processing technique in EIT.
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