umessen / body-and-organ-analysis Goto Github PK

Hello there!

When using the BOA PACS deployment, I observed that the output hierarchy is OUTPUT/ae_title/__/x_
instead of the StudyDate_AccessionNumber_StudyDescription and the corresponding tags for the series.

It seems to have trouble at the get_dicom_tags function. I this a known issue or a problem at my end?

Hello everyone,

We are in the process of getting the Docker up and running. However, it is not clear to us where exactly we should store the .env_sample? And what exactly do the parameters mean (e.g. CELERY_BROKER, RABBITMQ_USERNAME, RABBITMQ_PASSWORD, etc)?
Do these need to be integrated into our Python path?
Maybe you can help us with some more detailed installation instructions.

Many thanks and best regards

Matthias from Frankfurt

Hi there,

i've used the README for the env and docker-compose file.

When running docker compose up i get the following warnings:

WARN[0000] The "GIT_VERSION" variable is not set. Defaulting to a blank string. 
WARN[0000] The "PACKAGE_VERSION" variable is not set. Defaulting to a blank string. 
WARN[0000] The "GIT_VERSION" variable is not set. Defaulting to a blank string. 
WARN[0000] The "PACKAGE_VERSION" variable is not set. Defaulting to a blank string. 
WARN[0000] The "GIT_VERSION" variable is not set. Defaulting to a blank string. 
WARN[0000] The "PACKAGE_VERSION" variable is not set. Defaulting to a blank string.

Should i add GIT_VERSION and PACKAGE_VERSION to something in the env file and if yes what?

Cheers
Samuel from UKE Hamburg

Hello, thank you for the great work!

I experience a download error (for the totalsegmentator weights) after running docker run:

INFO:body_organ_analysis.commands:Image loaded and retrieved: DONE in 0.00003s
INFO:body_organ_analysis.compute.inference:Input image: /image.nii.gz
INFO:body_organ_analysis.compute.inference:Image size: (122, 101, 112)
INFO:body_organ_analysis.compute.inference:Image dtype: int32
INFO:body_organ_analysis.compute.inference:Voxel spacing: (3.0, 3.0, 3.0)
INFO:body_organ_analysis.compute.inference:Input Axcodes: ('R', 'A', 'S')
WARNING:body_organ_analysis.compute.inference:Unexpected CT values found in input image: got -1207.0-3382.0, expected -1024-3071. The values have been clipped to the expected range. Please check the segmentations to ensure that everything is correct.
INFO:body_organ_analysis.compute.inference:Computing segmentations for task total
INFO:totalsegmentator.libs:Downloading pretrained weights for Task 251...
Traceback (most recent call last):
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/app/body_organ_analysis/main.py", line 4, in
run()
File "/usr/local/lib/python3.8/dist-packages/body_organ_analysis/cli.py", line 168, in run
analyze_ct(
File "/usr/local/lib/python3.8/dist-packages/body_organ_analysis/commands.py", line 76, in analyze_ct
compute_all_models(
File "/usr/local/lib/python3.8/dist-packages/body_organ_analysis/compute/inference.py", line 123, in compute_all_models
download_pretrained_weights(tid)
File "/usr/local/lib/python3.8/dist-packages/body_organ_analysis/_external/totalsegmentator/libs.py", line 192, in download_pretrained_weights
download_url_and_unpack(WEIGHTS_URL, config_dir)
File "/usr/local/lib/python3.8/dist-packages/body_organ_analysis/_external/totalsegmentator/libs.py", line 77, in download_url_and_unpack
raise e
File "/usr/local/lib/python3.8/dist-packages/body_organ_analysis/_external/totalsegmentator/libs.py", line 64, in download_url_and_unpack
r.raise_for_status()
File "/usr/local/lib/python3.8/dist-packages/requests/models.py", line 1021, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 404 Client Error: Not Found for url: https://zenodo.org/record/6802342/files/Task251_TotalSegmentator_part1_organs_1139subj.zip?download=1

I checked the link and it works. This can happen due to an unstable connection on the server side and reaching timeout.
One of the possible solutions can be the increasing response waiting time. Or can you please provide the file structure that you expect in the weights directory, to have an opportunity to download the weights manually?

Thank you in advance.

To be able to use it on our gpu cluster the docker containers need to be offline (there is no internet connection available).
I can download, create and export the containers, but the problem is that the weights for the TotalSegmentator tasks don't download when setting up the containers.

I can try and put some test images like TCIA data through it but it seems like the real images we push to the BOA containers trigger more tasks than get downloaded for TCIA data. Can you provide a list of all the weights one needs to download to the weights folder to have full offline functionality? Or even better a script that downloads everything needed for offline-usage.

Cheers
Samuel from Hamburg