Title :
Electrical impedance tomography for human lung reconstruction based on TV regularization algorithm
Author_Institution :
Aeronaut. Autom. Coll., Civil Aviation Univ. of China, Tianjin, China
Abstract :
To solve the ill-posed problem in electrical impedance tomography (EIT) and overcome the blur effect made by conventional L2 Tikhonov regularization, a new two-step iterative regularization algorithm is applied for the process reconstruction of lung respiration. This algorithm is based on total variation (TV) regularization method, and uses a two-step iterative method with TV denoising operator, so that it can achieve double regularization effect. This algorithm has advantages in both resolution and robustness. Both simulation and experiment results are executed to prove the effectiveness of TV regularization method.
Keywords :
electric impedance imaging; image reconstruction; iterative methods; medical image processing; EIT; L2 Tikhonov regularization; TV regularization algorithm; blur effect; electrical impedance tomography; human lung reconstruction; ill-posed problem; iterative regularization algorithm; lung respiration; Conductivity; Electric variables measurement; Image reconstruction; Impedance; Iterative methods; TV; Tomography;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2012 Third International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-2144-1
DOI :
10.1109/ICICIP.2012.6391461