pydicom

To convert a DICOM file to PNG or JPEG, the Skill extracts the pixel data and applies VOI LUT windowing for correct grayscale or RGB display, then writes the output to standard image formats like PNG, JPEG, or TIFF.

Anonymizing DICOM metadata involves safely processing datasets to clear or modify common Protected Health Information (PHI) fields while maintaining correct UID and tag handling for compliant data sharing.

Extracting pixel arrays from multi-frame DICOM volumes requires loading the dataset and decoding compressed pixel data via appropriate transfer-syntax aware handlers like pylibjpeg or python-gdcm to access the underlying numpy arrays.

Yes, pylibjpeg works with pydicom for compressed pixel data decompression by acting as a transfer-syntax aware handler, specifically utilizing pylibjpeg-libjpeg and pylibjpeg-openjpeg to decode JPEG encoded medical imaging files.

DICOM images may display incorrectly if VOI LUT windowing is not applied during pixel data extraction, which adjusts the grayscale values for accurate visualization of medical imaging datasets.

Yes, you can export DICOM metadata to JSON by reading patient, study, series, and image tags from the dataset and extracting them into text or JSON formats for downstream clinical imaging pipelines.