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SUMMARY:Uncertainty Quantification of Inclusion Boundaries in the Context 
 of X-ray Tomography - Babak Maboudi Afkham (Technical University of Denmar
 k)
DTSTART:20210922T113000Z
DTEND:20210922T123000Z
UID:TALK162112@talks.cam.ac.uk
CONTACT:J.W.Stevens
DESCRIPTION:In my talk\, I will describe a Bayesian framework for the X-ra
 y computed tomography (CT) problem in an infinite-dimensional setting. We 
 consider reconstructing piecewise smooth fields with discontinuities where
  the interface between regions is not known. Furthermore\, we quantify the
  uncertainty in the prediction. Directly detecting the discontinuities\, i
 nstead of reconstructing the entire image\, drastically reduces the dimens
 ion of the problem. Therefore\, the posterior distribution can be approxim
 ated with a relatively small number of samples. We show that our method pr
 ovides an excellent platform for challenging X-ray CT scenarios (e.g. in c
 ase of noisy data\, limited angle\, or sparse angle imaging). We investiga
 te the accuracy and the efficiency of our method on synthetic data. Furthe
 rmore\, we apply the method to the real-world data\, tomographic X-ray dat
 a of a lotus root filled with attenuating objects. The numerical results i
 ndicate that our method provides an accurate method in detecting boundarie
 s between piecewise smooth regions and quantifies the uncertainty in the p
 rediction\, in the context of X-ray CT.\n\nJoin Zoom Meeting - https://mat
 hs-cam-ac-uk.zoom.us/j/96932950870?pwd=b1o2c2UxckVITlRlazJzY0laRmVHZz09\nM
 eeting ID: 969 3295 0870 Passcode: DRHjehPj
LOCATION:Virtual (see abstract for Zoom link)
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