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View Code? Open in Web Editor NEWApplication of Diffusion Probablistic Model for unsupervised OCT denoising
License: MIT License
Application of Diffusion Probablistic Model for unsupervised OCT denoising
License: MIT License
Hello, I want to use your pre-trained model to denoise my oct data set, but I see that your code is all in nii format, and my images are in png format. I don’t know how to modify it. to test directly on your pre-trained model. I would be grateful if you could answer me.
我不知道我的理解是否正确,我想我的训练集是原图,用来进行加噪扩散和逆向扩散,我的测试集则是有噪声的一些图片,是吗?我想我的训练集是4000张.png的图片,保存在一个路径中,测试集图片如上,我不知道该如何更改?以及您程序中E://中的tool我需要下载码?
Hi, I used your method to process other types of medical images, but the images sampled were gray. Do you know what happened
Hello! Great job!
I would like to ask you how to use three different levels of signal-to-noise ratio (92dB, 96dB, 101dB) to obtain pictures?
As you said in paper: To test the performance of the model at different speckle levels, the data is acquired with three different levels of signal-to-noise ratio (92dB, 96dB, 101dB).
I want to use my own dataset, but I don't know how to do this step, can you give some advice? Thank you very much!
Your readme should say what paper users should cite!
Maybe this one?
https://doi.org/10.1117/12.2612235
First of all, thank you very much for your work, I hope you can open source the complete code, including training, testing, etc. If it is not convenient to open source, Could you send it to me privately, thank you very much.
Hello Dewei,
thank you for sharing your work!
Is it possible to run your code on a custom Dataset? If yes, how would i manage this?
and what the input should be? How can i run your code?
Is there any requirement for the grayscale range of data?
Do I need to normalize the data to [0,1] ?
Thank you very much!
请问一般一轮训练的loss value一般为多少
Thank you for your excellent work and sharing the code.
Is the dataset in the paper public or private?
If it is public, can you provide the link to the dataset?
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