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FAQ regarding the usage of the dataset #8

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xinario opened this issue Jan 22, 2019 · 14 comments
Open

FAQ regarding the usage of the dataset #8

xinario opened this issue Jan 22, 2019 · 14 comments

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@xinario
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xinario commented Jan 22, 2019

  1. Which are the 850 images mentioned in your paper?
    Inside each experiment folder (SE0, SE1....SE28), there are 906 images. So to get the exact 850 images, you need to, first, reordering the image sequence according to the [SliceLocation] field of the Dicom image (sort in ascending order) and you will get images arranged from pelvis to head. Then just keeping slice 21 to 870 and discard the rest which has almost no content.

  2. What is the train/test split?
    After obtaining the 850 ordered images, test images were selected at an interval of 6, i.e. slice 1, 7, 13 … 847.

  3. How do you compute the PSNR and SSIM for the simulated and real dataset?
    For the simulated data, the generated noisy image was converted to uint8 using the abdomen window (center: 40, width: 400). The training and evaluation were all conducted using these narrow range 8 bit images.
    For the piglet data, the original 16 bit value was used. The training and evaluation was on 16 bit images.

  4. What should I do when my test dicom data is not uint16?
    In this case, the correct way to convert the data in preprocess.py is ([Hounsfield units]+1024)*22

@JackChan666
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I have been searching for the datasets, would you send me the datasets? Thank you very much!

@xinario
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xinario commented Apr 9, 2019

You can download the dataset from the below link:
https://docs.google.com/forms/d/e/1FAIpQLSdnIxHU-hX_fDC4FSqnTe_BbvF3MR4N1hkIMT0T5SHwcmqP0Q/viewform

@JackChan666
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Thank you very much!

@stefenmax
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But how to reorder the image sequence according to the [SliceLocation] field of the Dicom image,could u give more detailed information,cuz when i try to preprocess,the code cant detect the dicom file

@xinario
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xinario commented May 7, 2020

That info is in the dicom header. It can be extracted using package like pydicom. I would suggest you to review some dicom basics before proceeding.

@alexxony
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You can download the dataset from the below link:
https://docs.google.com/forms/d/e/1FAIpQLSdnIxHU-hX_fDC4FSqnTe_BbvF3MR4N1hkIMT0T5SHwcmqP0Q/viewform

i downloaded this link from onedrive. but it didnt unzip correctly. can you help me?

@xinario
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xinario commented Jul 22, 2020

Can you just try to redownload? I haven't get any issue like this before.

@alexxony
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Can you just try to redownload? I have get any issue like this before.

i tried to unzip in both windows and ubuntu.

But when in windows. it failed to start unzip

when in ubuntu. it failed to unzip during process.

  • another question.

i tried to install torch7 in ubuntu 20.04. but it failed to install and tf didnt work.

can i use pytorch instead of torch7?

@yuta0511
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yuta0511 commented Mar 7, 2022

I would like to use this data set. However, when I jump to the link, the image does not exist.

@Tihetna1891
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Tihetna1891 commented Apr 11, 2022

You can download the dataset from the below link: https://docs.google.com/forms/d/e/1FAIpQLSdnIxHU-hX_fDC4FSqnTe_BbvF3MR4N1hkIMT0T5SHwcmqP0Q/viewform

image
when I try to download using this link this happened ..please help me in getting the data

@sunyoungIT
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I want to get the dataset. but, the warning happened ... please help me in getting the data

@YuhangLiu98
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  1. The current folder is SE0-SE32, what are the changes with the previous one?

  2. What is the dose corresponding for each folder? Or what's the difference between each folder?

  3. There is a dose report in the file, but it does not correspond to the data set, which means it should need to be corrected?

@wpf756
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wpf756 commented Jun 11, 2024

  1. 当前文件夹是 SE0-SE32,与前一个文件夹有什么变化?
  2. 每个文件夹对应的剂量是多少?或者每个文件夹之间有什么区别?
  3. 文件中有剂量报告,但它与数据集不对应,这意味着它应该需要更正?
    解决了吗

@yanghccc
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  1. 当前文件夹为 SE0-SE32,与上一个文件夹有什么变化?
  2. 每个文件夹对应的剂量是多少?或者每个文件夹之间有什么区别?
  3. 文件中有剂量报告,但与数据集不对应,这意味着应该需要更正吗?

同问解决了吗

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