neheller / kits21 Goto Github PK

Hi, thanks for your codes;
how train and test on some samples?
is there any trained model?

Kindly add the dataset description to the repo (e.g., number of cases, demographics, etc.)

Can someone help me with this. I cloned the repo, ran the get_imaging.py file. initially I want to check the dataset so that is why I only ran for 10 cases. But every time there is this error below-

HTTPSConnectionPool(host='kits19.sfo2.digitaloceanspaces.com', port=443): Max retries exceeded with url: /master_00000.nii.gz (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x000001E915A80430>: Failed to establish a new connection: [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond'))

Would appreciate if I can get an immediate help in this regard. TIA.

Hi,

I followed Usage and when I run python3 kits21 / starter_code / get_imaging.py in my terminal I got this error: ModuleNotFoundError: No module named 'requests'.

I'm not very experienced so I'm not sure I'm doing it right or understanding all of this.

Any idea ?

Hi, I've noticed that my results with Baseline Model (Described here) are inconsistent with those described in this repository.

I used the unchanged KiTS21 Dataset and ran predictions with the 3d_fullres Baseline model without changes in weights. However, after running sample_segmentations and evaluate_predictions, I got different results that are described in this repository and paper. All source code I left unchanged (that counts for seeds for randomization).

Do you know any particular reason why this can happen?

It's not necessary for every saved json file to be stored. The most recent one for each instance should contain all necessary information about the edit lineage. The remainder can be discarded by the annotation/import.py script.

Hello,

I am trying to understand how to compare (or merge) the datasets of kits19 and kits21. The description of the classes in the kits21 webpage (https://kits21.kits-challenge.org/) says that the kidney class should be equivalent for both, however I thought, reading the kits19 data description paper (https://arxiv.org/pdf/1904.00445.pdf, page 4, bullet point 2), that cysts were included in the kidney class for kits19, in which case it would be equivalent to kidney + cysts in kits21?

Thanks!

Hello,
recently I tried to add some clinical CTs from hosipitals into KiTS. However I noticed KiTS nii fomat shape be like (num_slices, height, width) , which can be described as (z, x ,y) and origin be like(0,0,0). But my CTs get (x, y ,z) shape and have none-zero origins. One way to solve this problem is that I transposed the dims, pixdims. But how to deal with the qform/sform , origin and srow_x/y/z in the metadata still confuse me.

Hi and a very good day,

Thank you for organising this challenge and in turn providing the annotated datasets.

I have a question here, if I would want to remove the cyst label from the segmentation mask, eg: the majority voting of aggregated_MAJ_seg.nii.gz, how can I perform such action?

I have tried manually removing the label 3 (assuming that cyst label is represented by label 3) with ITK snap's Label Editor, but however it does not seem to be able to remove it after I reopen the edited mask.

Would you please give some guidance on this

Best regards,
Danny

Hi!
When accessing the links from the KiTS21 website to see the papers from openreview, the following message appears:

Could you provide aggregated segmentation, with ureter,artery,vein etc.. ,besides kidney and tumor?

hi！recently i have been working on no-contrast CTs(more than 300) kidney segmentation，while 90% of them get very bad performance on KiTS.
it confused me and I have checked the two datasets ，both KiTS and mine ，to ensure they remain highly consistent expect for differences in kidney HU intensity.
I do have some other CTs with contrast (just like the KiTS) and the fact is that when do the inference on kidney filled with medium, KiTS model demonstrats outstanding performance but it fails to segment a whole kidney in no-contrast CTs.
is there any chance that KiTS21/19 model rely on high HU intensity too much to make judgments using contrast，while hardly capturing other features such as position and shape so that when medium disappears the model cannot recognize kidneys?

Hello,

I might be doing something silly, but I used the bash option get_imaging.sh and it only downloads the imaging.nii.gz files. How do I get the labels (segmentations)? I tried installing but pip install always result in errors.

Thanks,
Lorena

Hello,

I meet a problem after I run get_imaging.py. In my downloaded data folder, it seems imaging.nii.gz is missing. I would like to ask how can I access the imaging.nii.gz files? Hope for your reply :)

I got 300 scans at all, and how can I split them into training and testing sets?

Hello,
I have successfully run the get_Imaging.py file and got the image.nii.gz under the corresponding case folder. But the each image.nii.gz looks strange. Their grayscale values are almost all zero, with some very small negative numbers. That means when I opend the image.nii.gz by ITK-SNAP, I can not see the any useful image information.

Hello, I am working on data collection for my research and I need CT scan images of patients with chromophore renal cell carcinoma and benign renal oncocytoma. Can I get data for these conditions, please? On your site I saw images but where is the type of cancer?? is there any excel sheet??

I seem to be unable to run the get_imaging.py script to load the images.

Hi Nick, excellent work with KiTS21 :)

I noticed that Instance 1 Cyst and Instance 3 Tumor refer to the same structure in case 00205, is that intended?. Considering that there was no Tumor region in KiTS19 I guess it is supposed to be a cyst.

Best,
Michael

Is it possible to get another implementation of get_imaging in Julia?

Can the annotation be used as segmentation classes?

you have 3 segmentation clases (Kidneys, tumor,cyst) but you have more annotation in the RAW folder (Arteries,veins,unretires) how can I make use of theses?

Hello, I am having problem with just training the dataset with baseline nnUnet.
Fabian has kindly written the conversion of dataset python file, and I just used it to
convert kits 21 dataset. However following error occurs during preprocessing.

RuntimeError: Exception thrown in SimpleITK ImageFileReader_Execute: /tmp/SimpleITK/Code/IO/src/sitkImageReaderBase.cxx:105:
sitk::ERROR: Unable to determine ImageIO reader for "/home/mchangaf/nnUNetFrame/DATASET/nnUNet_raw/nnUNet_raw_data/
Task135_KiTS2021/imagesTr/case_00038_0000.nii.gz"

On certain files, Exception thrown in SimpleITK ImageFileReader occurs. Should I just ignore these errors and continue training?

There is a error occured when i try to download this dataset, log was that ...
...
300 cases to download...
1/300...
check_hostname requires server_hostname
...
thanks,

Hi.

I ran

python kits21/annotation/sample_segmentations.py
python kits21/evaluation/evaluate_predictions.py output

Then it gets me

multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
  File "/opt/conda/lib/python3.8/multiprocessing/pool.py", line 125, in worker
    result = (True, func(*args, **kwds))
  File "/opt/conda/lib/python3.8/multiprocessing/pool.py", line 48, in mapstar
    return list(map(*args))
  File "/workspace/kits21/kits21/evaluation/metrics.py", line 200, in evaluate_predicted_file_on_samples
    raise RuntimeError('segmentation_samples folder missing. Please run kits21/annotation/sample_segmentations.py')
RuntimeError: segmentation_samples folder missing. Please run kits21/annotation/sample_segmentations.py
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "kits21/evaluation/evaluate_predictions.py", line 29, in <module>
    evaluate_predictions_on_samples(args.folder_with_predictions, args.num_processes)
  File "/workspace/kits21/kits21/evaluation/metrics.py", line 168, in evaluate_predictions_on_samples
    metrics = p.map(evaluate_predicted_file_on_samples, predicted_segmentation_files)
  File "/opt/conda/lib/python3.8/multiprocessing/pool.py", line 364, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()
  File "/opt/conda/lib/python3.8/multiprocessing/pool.py", line 771, in get
    raise self._value
RuntimeError: segmentation_samples folder missing. Please run kits21/annotation/sample_segmentations.py

I read link, and I'm not sure why I should run python kits21/annotation/sample_segmentations.py. Okay you said, this is about 5-fold CV. And the description in the kits21/evaluation/evaluate_predictions.py says whatever in the directory output will give us the result.