Dr Shangjie Ren
Fri 10 Mar 2017, 13:00 - 14:00
AGB seminar room

If you have a question about this talk, please contact: Jonathan Mason (s1015431)

Image for Boundary Element and Shape Inversion Methods in Electrical Tomography

Abstract: Electrical Tomography is a non-invasive or non-intrusive process visualization technology to image the internal
conductivity distribution from the boundary electrical measurements. Due to its advantages of no radiation, high speed and
low cost, it has been well studied and successfully applied in many industrial or biological processes. However, due to the
non-linear and ill-posed character, the spatial resolution of Electrical Tomography is low. By far, the most commonly used
reconstruction algorithms in Electrical Tomography are pixel/voxel based, in which the distribution of the electrical
parameter are discretized into finite number of volume elements and then reconstructed by optimizing the fit of the
simulated to measured boundary data. These methods are suitable for imaging the mixed materials with indefinable
interfaces, such as flames in porous media. For the applications involving piecewise constant conductivity distribution,
such as flammable liquids detection and oil transportation, it is difficult to obtain high spatial resolution images due to the
inherent limitations of the pixel/voxel based methods. To overcome the problem, some shape based reconstruction
methods are developed. These methods parameterize the conductivity by the boundaries of the piecewise subdomains,
and directly reconstruct the shapes of the subdomains from the electrical measurements. And a result, the dimensions of
the reconstruction problem is reduced, and the ill-posed character is mitigated. Based on the numerical and experimental
testes results, the shape inversion is better than the pixel-based method in some special application cases. To improve
the development of shape based method, a unify shape inversion platform is developed, and open source fro every
researches in related fields.


Biography: Shangjie Ren graduated from Tianjin University with a bachelor degree in Electrical Engineering in 2008. After
that, he carried out research in Electrical Tomography at the same university, and received his Ph.D. degree in 2013.
During 2015 to 2016, he worked as a post-doctoral scolar in Stanford University (USA) in the field of Multi-paremteric and
Multi-modality Imaging. At present, he is a lecturer in Tianjin University and doing the researches on Electrical Tomography,
Boundary Element Method, Shape Inversion Method, and Multi-modality Tomograpy. Dr. Ren has published many
research articles in international journals and conference proceedings. His Ph. D. Dissertation ‘Shape Reconstruction
Method in Electrical Tomography’ was awarded ‘The Best Doctoral Thesis’ in 2015 by his University. He believes that
Shape Inversion and Multi-modality Tomogrpahy will blaze a new trail for improving the spatial resolutions of Electrical
Tomography.