人体肺功能生物电阻抗成像技术

Lung Functional Imaging Based on Medical Electrical Impedance Tomography

研究的目的在于改进生物电阻抗(EIT)重建图像质量方法。首先,采用自适应多重网格法,依据后验误差的估计,基于自适应网格剖分加速线性方程组的求解,并根据多重网格算法细分相关场域,获得圆形场域的人体呼吸过程图像;然后,研究结合先验知识的图像重建算法,根据肺部组织结构及阻抗特性,采用有限元仿真软件COMSOL求解正问题,获取融合先验知识的灵敏度系数矩阵。人体肺呼吸功能实时成像结果表明,即使采用较少的网格单元,仍可获得较高精度的正问题解,具有较高的图像质量。

A new image reconstructed algorithm was presented for the medical electrical impedance tomography（EIT）.First the adaptive multi-grid algorithm was employed by which the sequence of computational grids was successively refined through the posterior error and the adaptive grids refinement,the lung ventilation was imaged considering the field as circle.Then the sensitivity matrix was solved by commercial simulation software COMSOL considering the structure and resistivity of lung,the prior information was adopted to reconstruct the lung conductivity distribution.On the lung ventilation imaging system,two steps were available to reconstruct the functional respiration process image in real-time.The images indicated that a higher accuracy solution of the forward equation and the higher spatial resolution of images could be achieved.