I try to use the default set, But the result is far from the paper

[sailuluo]

for cardiac dataset. and use default.nii. when validation, I modify part of the code to evaluate the zero-fillied image with ground truth. result is: Evaluating 0300 psnr(before|after) = 36.63|35.94 ssim = 0.9410|0.9089 Done

compare with after, before just missing an imaginary part.

why the zero-fillied image without reconstruction can achieve higher PSNR score？ then I evaluate 10% sample ratio, 5% sample ratio, all PSNR and SSIM are higher.

 

[sailuluo]

I train with the default set, the DC_CNN result far from paper's result

[tinyRattar]

So, u mean that the real part has higher PSNR than the result of network? Would u like to share some more like modified code?

For you second question, do u mean that DC_CNN should result to higher PSNR? But the default config file in this repo works for the proposed model not DCCNN, or u just use the config file from storage repo? Anyway, the PSNR result is too higher than exception, no mattar DCCNN or proposed. So would u like to share more information, like the config file, experiments? Thank u so much.

[sailuluo]

hello, I finally find the reason. the dataset processed by the convert code not same as that you provide. The result is normal after using the dataset you provided