Open jithenece opened 3 months ago
This model was trained on the LiTS 2017 dataset. The liver is a common site of primary (i.e. originating in the liver like hepatocellular carcinoma, HCC) or secondary (i.e. spreading to the liver like colorectal cancer) tumor development.
@LennyN95
Could you add common entry for tumor in segdb so that LIVER+TUMOR
can be used here? It has both primary and secondary tumor.
@jithenece can you use NEOPLASM_MALIGNANT
as the custom roi? the model output isn't specific to colorectal cancer liver lesions.
/review
@LennyN95 could you please review this.
/test
sample:
idc_version: "Data Release 2.0 April 25, 2023"
data:
- SeriesInstanceUID: 1.3.6.1.4.1.14519.5.2.1.9203.8273.254242588659825836950462054011
aws_url: s3://idc-open-data/a192c6ca-69b0-4195-bfa5-4fe9962b2da6/*
path: dicom
reference:
url: https://drive.google.com/file/d/1id1W7sXydHq52NTKa8GJqRycatyhkQaR/view?usp=sharing
Generating segmentation permanent link for testing output.zip
sample: idc_version: 15.0 data:
/test
sample:
idc_version: 15.0
data:
- SeriesInstanceUID: 1.3.6.1.4.1.14519.5.2.1.9203.8273.254242588659825836950462054011
aws_url: s3://idc-open-data/a192c6ca-69b0-4195-bfa5-4fe9962b2da6/*
path: input_data
reference:
url: https://github.com/user-attachments/files/16762679/output.zip
missing_files: - case_study1/flair.seg.dcm
Could you provide verbose logs from the docker to check the issue. I could see case_study1/flair.seg.dcm
which is related to brain-mr is listed here.
@jithenece maybe some files were included in the reference by mistake? I updated the test pipeline during the past week which now is drastically simplified. It will require some minor updates and I hope simplified procedure makes up for that ;)
Please note, we updated our base image. All mhub dependencies are now installed in a virtual environment under /app/.venv
running Python 3.11
. Python, virtual environment and dependencies are now managed with uv. If required, you can create custom virtual environments, e.g., uv venv -p 3.8 .venv38
and use uv pip install -p .venv38 packge-name
to install dependencies and uv run -p .venv3.8 python script.py
to run a python script.
We also simplified our test routine. Sample and reference data now have to be uploaded to Zenodo and provided in a mhub.tom file at the project root. The process how to create and provide these sample data is explained in the updated testing phase article of our documentation. Under doi.org/10.5281/zenodo.13785615 we provide sample data as a reference.
@LennyN95 I have updated the test files in the required format. Could you share the Test results
if this fails.
Pretrained model for 3D semantic image segmentation of the liver and liver lesions from ct scan