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[ICLR2023] Official repository of DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models

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Hi, I have 2 questions regarding the datasets: 1- Can DDM2 be run with multi-shell datasets? I see in the paper that DDM2 was run with: - Hardi with b-value=...

Hi, thank you for this amazing paper. I wanted to ask you very few questions to elaborate in very detail. Should the data used for training during the training process...

HI, Great work and great paper, I'm wondering if you are open for other researchers to cross-validate and then work along this direction, maybe you can provide a sample dataset...

Hi, thanks for publishing the code! I am trying to implement your code on other MRI modalities, whose noise levels may be less series than DWI images. However, I found...

Hi, I looked closely at the posted code and noticed that the sampling process is different from the original DDPM and the labels for the training process are different, the...

Hi, I'm having trouble understanding stage 3, can you give a brief description of how stage 3 works and what does continuous_sqrt_alpha_cumprod do once it's passed into the network?

Hello, Thanks for making this tool available. When I processed the Hardi_150 example following your instructions, the denoised image has a spatial resolution of 1x1x1 mm^3. However, the input image...

I'm having difficulty understanding the code you provided. Could you please clarify the following points for me? 1. Does x_noisy represent noisy images at different steps t? 2. Is x_recon...

I encounter some trouble when trying to read your code. I plan to change the dataset to my version, but I do not understand what does 'condition' mean? Could you...

Can I ask what is the correct shape for matched state? I Originally thought it should be an integer referred to t, but it's not correct.