Dicom Processing Tool

• This builds ontop of the original Niffler toool the group used
• Code is reduced/modified so that extraction of PNGS/Tomo/CT/MRI are in a single interface with up todate dependenceis

Installation

• Have an enviroment with python 3.11 installed

    cd /path/To/Repo
    python3 -m pip install -r ./reqs.txt 
    python3 -m pip install -e .     

Running Extraction

    python3 -m A3IDicomTools.DicomExtract --ConfigPath ./YourConfig.json

{
"DICOMHome": "DummyPath",
"OutputDirectory": "DummyStuff",
"SaveBatchSize": 500,
"PublicHeadersOnly": true,
"SpecificHeadersOnly":false,
"SaveImages": true,
"ApplyVOILUT":true,
"NumProcesses": 12 ,
"Extractor":"General"
}

Parameters Explained

• SaveBatchSize: Sometimes dicom tags are excessively large. As a workaround we save batches of metadata with batchSizes (100-200)
• SaveImages: Save the images. If set to False no images are saved
• PublicHeadersOnly: If set to false we will also output Private dicom tags. 99.9% of the time private tags are not used
• SpecificHeadersOnly: DONOT modify
• NumProcesses: Number of processes to use for parallel extraction. Warning more does not always mean better.
• ApplyVoiLut: Apply Windowing operation only used for mammograms and x-ray images
• Extractor: Type of extractor to use Currently support
  • "General" Will run extraction of all the images. Will apply unique processing to MRI/CT,X-ray,Tomogram
  • Other modalities will be ignored for now
• ApplyParentFilter: Should only be set to true if running extraction CT/MR images. Since it will filter studies in the following way /patient/study/series/f1.dcm /patient/study/series/f2.dcm if set to true we will only read 1 dcm file. making the metadatafile like this /patient/study/series/f1.dcm
• Reorient: When making niftis we usually reorient to RAS orientation. This is set to True as the default to maintain consistency with older projects

Differences from Niffler extraction code

• When extracting NIFTI's the column 'file' will be the path to the dicom file used to extract metadata. Old extractions would have the directory to the series
• image_path: the hashing for the nifti file has been updated to be the path of the dicom file. This avoids issues with overlapping ids in some rare cases
• There is no mapping file. the metadata file contains an 'image_path' column.
• Failed extractions WILL HAVE NaN 'image_path' columns. So you must drop them.
• Based on the dataset available to you. there will be pngs and niftis in the file. You must filter accordingly.