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Recent Updates

Casper da Costa-Luis edited this page Sep 30, 2024 · 16 revisions

Here you find the recent updates of our challenge:

Sept 30

September 25

September 21

September 10

  • Mediso AnyScan NEMA IQ data now complete and zip file available

September 9

September 3

  • We have identified a lower precision issue with the calculation of the value of the RDP: it is returned to Python at float precision as opposed to double. This could affect algorithms which do line searches (when close to convergence). The gradient of the RDP is not affected. Please let us know if this is a problem for you and we can fix the underlying SIRF issue. See #100 for more details.

August 23

August 21

  • corrected RDP formula on the wiki: add a factor 1/2 (#87)

July 10

  • reference images and VOIs have been added for the NeuroLF and mMR datasets
  • petric.QualityMetrics implement the metrics as a callback. These are now added to the leaderboard.
  • edge-gpu image now has a CUDA version of RelativeDifferencePrior (previous version was using the CPU version, which is a lot slower).
  • petric.get_data now returns VOIs, and uses the CUDA RelativeDifferencePrior if it's available.

June 28

  • The registration for the challenge has opened! Join now!
  • There are currently three datasets available on https://petric.tomography.stfc.ac.uk/data. They do not have any region-of-interests nor the reference image yet but these will be added soon. More datasets will follow.
  • We have not yet created a final release of SIRF for the challenge. Therefore, if you want to get going, use the edge or edge-gpu Docker build. When building manually, use the master branch of the SIRF-SuperBuild.
  • While we have defined the metrics for evaluation (see the main wiki page), the final thresholds used in the competition will be provided in the following weeks.

July 2

  • NeuroLF data has been corrected. Headers for all OSEM_image.hv are now more complete.
  • edge-gpu image now has the CUDA version of parallelproj (previous version was using the CPU version, which is a lot slower)