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A Wolfram Mathematica image processing code for particle flow images with low SNR/CNR (originally high-FPS neutron imaging).

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Low_C-SNR_Particle_Detection

A Wolfram Mathematica image processing code for particle flow images with low SNR/CNR.
Originally developed for high-FPS neutron imaging in liquid metal in presence of "phantom particles" stemming from correlated noise.

The methodology, implementation, applications and validation are showcased in the following articles:
"Particle tracking velocimetry in liquid gallium flow about a cylindrical obstacle"
https://link.springer.com/article/10.1007/s00348-022-03445-2
"Particle tracking velocimetry and trajectory curvature statistics for particle-laden liquid metal flow in the wake of a cylindrical obstacle"
http://dx.doi.org/10.48550/arXiv.2206.11033

ATTENTION: the post-processing part of the code uses a package https://github.com/antononcube/MathematicaForPrediction/blob/master/QuantileRegression.m
by Anton Antonov (antononcube)
https://github.com/antononcube

Q: How does one use the code?
A: Instructions soon to be posted here.

Q: Is there an example dataset to test the code?
A: One will be made public soon, with examples of output.

Q: Am I available to help apply the code to your problem?
A: Yes, feel free to contact me at mihails.birjukovs@lu.lv or michael.birjukov@gmail.com

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A Wolfram Mathematica image processing code for particle flow images with low SNR/CNR (originally high-FPS neutron imaging).

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