An Image Reconstruction Simulation Based on Prior Information for the Pulmonary Electrical Impedance Tomography

Abstract:

In electrical resistance tomography (ERT), one of the main reasons for poor quality of reconstructed image is ill-posed property of the inverse problem. In order to improve image quality, one of the feasible methods is to incorporate prior information. Based on conventional Tikhonov regularization method to reconstruct ERT image, the regularization matrix, combined with prior information vector, was proposed. The prior information included the structure property of human thorax, conductivity distribution information of organs and other dynamic information during the respiration process. The research results indicated that the proposed method can enhance the spatial resolution of the reconstructed images, and reduced the trail traces of the investigated objectives. It is promising in detecting and monitoring regional lung ventilation change by means of the ERT system with a proper imaging method.

• Periodical: Advanced Materials Research (Volume 748)
• Pages: 655-658
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.748.655
• Online since: August 2013
• Authors: Shi Hong Yue, Jin Xin Zhang, Xiu Juan Bao
• Keywords: Electrical Resistance Tomography, Image Reconstruction, Lung Function, Prior Information, Tikhonov Regularization

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