基于TwIST-TV正则化算法的肺萎陷电阻抗成像仿真研究

doi:10.3969/j.issn.0258-8021.2013.01.001

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Abstract Thoracic electrical impedance tomography (EIT) is a noninvasive, radiationfree monitoring technique for reconstruction of the crosssectional image of the internal spatial distribution of conductivity from electrical measurements made by injecting small alternating currents via an electrode array placed on the surface of the thorax. To solve the illposed problem of EIT, a twostep iterative shrinkage/threshholding algorithm (TwIST) based on total variation (TV) regularization was proposed in this paper. This algorithm used an iterative method with TV denoising operator, so it can achieve double regularization effect. Three dimensional (3D) EIT models of collapsed lung under different conditions were built up, and this algorithm was adopted to reconstruct differential images of respiratory status. And EIT derived numeric index was also employed for evaluation of lung ventilation. The results showed that the TV-TwIST method can further improve image quality and stability compared with traditional Tikhonov regularization method. And the corresponding evaluation index based on
TV-TwIST algorithm also behaved better than that based on Tikhonov regularization. Therefore, the results verified the feasibility of this algorithm applied to clinical use for ventilation monitoring of patients with collapsedlung.

Key words： electrical impedance tomography inverse problem TV regularization ventilation index

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	FAN Wen Ru^1*WANG Hua Xiang²HAO Kui Hong¹MA Min¹

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FAN Wen Ru^1*WANG Hua Xiang²HAO Kui Hong¹MA Min¹. Simulation Study on Electrical Impedance Tomography of Collapsed Lung Based on TwIST-TV Regularization Algorithm[J]. journal1, 2013, 32(1): 1-6.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2013.01.001 OR http://cjbme.csbme.org/EN/Y2013/V32/I1/1

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