bbbbbbzhou / dudornet Goto Github PK

作者您好，我想用您的代码仅用来测试，能不能提供一下训练过后的参数文件和测试数据呢？

I have trained your model from the scratch, but at the first 7 epochs (up to now), the images generated are strange, very different from the target images, and i cannot see any tissue structure, is that right?

As shown in the above picture, the dimensions of x_I that I am going to input into the model are [3, 2, 320, 230]， 3---batch_size, 2---num_channels, 320---height, 230---width

And I find when x_I comes to self.net_G_I, it equals to x comes to self.SFENET1. However, it occurs the strangest thing that the size of x becomes [3, 2, 320, 230, 2] ( at this time, the model has not worked on x), and I am sure there is no obvious operation in these codes to change the size of x_I or x before the model's work.

I look into x[:, :, :, :, 1], and I find x[:, :, :, :, 1] is totally a zero matrix as this picture:

I am so confused by why the dimension increases from x_I to x, and I would appreciate it if you could answer me.

Hello author, two masks radial and spiral are mentioned in the paper, but there is only Cartesian mask generation method in the repository, may I ask how to make these two masks?

Hi! Thanks for your great work.

I am currently also working on deep learning-based MRI reconstruction and I am using DuDoRNet as the reconstruction network. I noticed that in the codebase, the network uses a special weight initialization, rather than the default initialization of pytorch. I am wondering why? Cause I found that if I used the default initialization, the convergence of the network became faster.

Dear author,

As the CVPR is on going, what's your plan to open-source the code?

Bests

Hello author！In the definition of fft2 (the same as ifft2) in the utils module, why do I need ifftshift( ) and fftshift( ) before and after torch. fft( the same as torch.ifft )? I don't quite understand this, can you help me explain it?