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SUMMARY:A Data-Driven Edge-Preserving D-bar Method for Electrical Impedanc
 e Tomography - Siltanen\, S (University of Helsinki)
DTSTART:20140210T153000Z
DTEND:20140210T161500Z
UID:TALK50753@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-authors: Sarah Hamilton (University of Helsinki)\, Andreas 
 Hauptmann (University of Helsinki) \n\nElectrical Impedance Tomography (EI
 T) is a non-invasive\, inexpensive\, and portable imaging modality where a
 n unknown physical body is probed with electric currents fed through elect
 rodes positioned on the surface of the body. The resulting voltages at the
  electrodes are measured\, and the goal is to recover the internal electri
 c conductivity of the body from the current-to-voltage boundary measuremen
 ts. The reconstruction task is a highly ill-posed nonlinear inverse proble
 m\, which is very sensitive to noise\, and requires the use of regularized
  solution methods. EIT images typically have low spatial resolution due to
  smoothing caused by regularization. A new edge-preserving EIT algorithm i
 s proposed\, based on applying a deblurring flow stopped at minimal data d
 iscrepancy. The method makes heavy use of a novel data fidelity term based
  on the so-called CGO sinogram. This nonlinear data preprocessing step pro
 vides superior robustness over traditional EIT data formats such as curr e
 nt-to-voltage matrix or Dirichlet-to-Neumann operator.\n\nRelated Links: h
 ttp://arxiv.org/abs/1312.5523 - Arxiv preprint \n
LOCATION:Seminar Room 1\, Newton Institute
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