Dear @daviddmc,
Thank you for this open source code!
I try to reproduce your experiments by computing the PSNR score between the reconstructed volume from NeSVoR and the original high resolution data that I sub-sampled.
I get surprisingly low PSNR value, that seem to be due to a shift in the intensity distributions between the two images.
By searching in the code, I did identify the line 525 in svort/inference.py , (function run_svort) which looks like a normalization of the intensities and could thus induce the shift in the distribution.
Could you please explain me why the normalization at line 525 is needed, and how you did handle the problem of shift in the distribution for computing the PSNR in your paper?
Thanks very much for your help
Best,
Steven
Dear @daviddmc,
Thank you for this open source code!
I try to reproduce your experiments by computing the PSNR score between the reconstructed volume from NeSVoR and the original high resolution data that I sub-sampled.
I get surprisingly low PSNR value, that seem to be due to a shift in the intensity distributions between the two images.
By searching in the code, I did identify the line 525 in svort/inference.py , (function run_svort) which looks like a normalization of the intensities and could thus induce the shift in the distribution.
Could you please explain me why the normalization at line 525 is needed, and how you did handle the problem of shift in the distribution for computing the PSNR in your paper?
Thanks very much for your help
Best,
Steven