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SUMMARY:Rich and non-rich tomography with the Core Imaging Library - Jakob
  Jørgensen (Technical University of Denmark)
DTSTART:20230301T150000Z
DTEND:20230301T160000Z
UID:TALK197950@talks.cam.ac.uk
DESCRIPTION:A variety of challenging tomography problems have emerged in r
 ecent years and their solution call for joined-up work on the underlying m
 athematics\, the algorithms as well as the numerical software. With the ho
 pe to facilitate this process\, we have developed the Core Imaging Library
  (CIL) &ndash\; a python package for the solution of rich and &ldquo\;non-
 rich&rdquo\; tomography and other inverse problems (https://ccpi.ac.uk/cil
 /). As an example of rich tomography\, I will describe our recent work on 
 hyperspectral neutron tomography. Here\, we developed a spatio-spectral re
 construction method in CIL for separating materials based on Bragg edges i
 n energy-resolved neutron data. As an example of &ldquo\;non-rich&rdquo\; 
 tomography\, I will describe a directional total variation reconstruction 
 method implemented in CIL and submitted as an entry to the recent Helsinki
  Tomography Challenge 2022 for limited-angle X-ray CT reconstruction. Fina
 lly\, participants are invited to our upcoming&nbsp\;training&nbsp\;and ha
 ckathon to try out CIL for their own rich (and non-rich) tomography proble
 ms in Cambridge this March (https://ccpi.ac.uk/events/byod-cil-hackathon/)
 .
LOCATION:Seminar Room 2\, Newton Institute
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