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surajpaibLennyN95
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Update zenodo sample testing for FMCIB and add file annotations (#107)
Co-authored-by: Leonard Nürnberg <[email protected]>
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models/fmcib_radiomics/config/default.yml

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targets:
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- csv-->[i:sid]/features.csv
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# - nifit:mod=seg:origin=dicomseg-->[i:sid]/masks/[basename]
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# - nifti-->[i:sid]/nifti/[d:mod]/[basename]
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# - nifti-->[i:sid]/nifti/[d:mod]/[basename]
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sample:
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input:
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dicom/: Dicom files of the CT scan and the DICOMSEG file containing the segmentations.
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dicom/1.3.6.1.4.1.14519.5.2.1.4334.1501.312037286778380630549945195741/1-1.dcm: DICOMSEG file (arbitrary file name)
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dicom/1.3.6.1.4.1.14519.5.2.1.4334.1501.312037286778380630549945195741/0.dcm: CT slice (arbitrary file name)
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dicom/1.3.6.1.4.1.14519.5.2.1.4334.1501.312037286778380630549945195741/1.dcm: CT slice (arbitrary file name)
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output:
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1.3.6.1.4.1.14519.5.2.1.4334.1501.312037286778380630549945195741/features.csv: The CSV file containing a set of features extracted from the input CT image

models/fmcib_radiomics/config/from_centroids.yml

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@@ -18,3 +18,11 @@ modules:
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DataOrganizer:
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targets:
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- csv-->[i:patientID]/features.csv
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sample:
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input:
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LUNG1-001/: A folder named after a instance identifier LUNG1-001
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LUNG1-001/centroids.json: A file named centroids.json containing the centroids of the ROIs per instance
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LUNG1-001/CT.nrrd: A nrrd file named CT.nrrd containing the CT image per instance
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output:
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LUNG1-001/features.csv: The CSV file containing a set of features extracted from the input CT image per instance

models/fmcib_radiomics/config/from_json.yml

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DataOrganizer:
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targets:
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- csv-->[i:sid]/features.csv
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sample:
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input:
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1.3.6.1.4.1.32722.99.99.298991776521342375010861296712563382046.json: Json file with centroids named by the SeriesInstanceUID of the related CT image
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CT_1.3.6.1.4.1.32722.99.99.298991776521342375010861296712563382046/: Input directory
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containing the CT image
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output:
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1.3.6.1.4.1.32722.99.99.298991776521342375010861296712563382046/features.csv: The CSV file containing a set of features extracted from the input CT image

models/fmcib_radiomics/config/from_nifti_mask.yml

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DataOrganizer:
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targets:
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- csv-->[i:patientID]/features.csv
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sample:
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input:
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lung_001/CT.nii.gz: A nifti file named containing the CT image per instance
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lung_001/masks/GTV.nii.gz: A nifti file with a binary gtv label map which center is used as seed point
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output:
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lung_001/features.csv: The CSV file containing a set of features extracted from the input CT image

models/fmcib_radiomics/config/from_rtstruct.yml

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DataOrganizer:
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targets:
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- csv-->[i:sid]/features.csv
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# - nifti-->[i:sid]/nifti/[d:mod]/[basename]
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# - nifti-->[i:sid]/nifti/[d:mod]/[basename]
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sample:
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input:
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RTSTRUCT_1.2.246.352.71.2.494841863751.4253616.20190218155318/: Arbitrary input directory
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containing the RTStruct dicom file
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CT_1.3.6.1.4.1.9590.100.1.2.170217758912108379426621313680109428629/: Arbitrary input directory
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containing the CT image
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output:
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1.3.6.1.4.1.9590.100.1.2.170217758912108379426621313680109428629/features.csv: The CSV file containing a set of features extracted from the input CT image

models/fmcib_radiomics/config/from_slicer.yml

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@@ -18,3 +18,10 @@ modules:
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DataOrganizer:
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targets:
2020
- csv-->[i:patientID]/features.csv
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sample:
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input:
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1.3.6.1.4.1.32722.99.99.239341353911714368772597187099978969331/0 Unnamed Series.nrrd: A nrrd file named containing the CT image per instance
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1.3.6.1.4.1.32722.99.99.239341353911714368772597187099978969331/F.mrk.json: A slicer markup file named containing seed point for the ROI
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output:
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1.3.6.1.4.1.32722.99.99.239341353911714368772597187099978969331/features.csv: The CSV file containing a set of features extracted from the input CT image

models/fmcib_radiomics/mhub.toml

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[model.deployment]
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test = "https://zenodo.org/records/14205464/files/test.zip"
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test = "https://zenodo.org/records/14947770/files/test_fmcib_latest.zip"

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