pydicom

To extract pixel data from DICOM files, this Skill processes CT, MRI, and X-ray datasets by parsing the medical imaging data and preparing it for visualization using libraries like numpy and matplotlib.

Anonymizing patient metadata in medical imaging datasets involves accessing and modifying specific DICOM tags. This Skill provides programmatic tools to alter attributes within CT and MRI scans to protect patient information.

Yes, you can convert DICOM images to PNG format. This Skill extracts the medical imaging pixel data and utilizes the pillow library to save the scans as standard image files for presentations.

Yes, pydicom supports reading and writing DICOM files. This Skill leverages the library to load, inspect, and save medical imaging datasets, handling standard formats like CT, MRI, and X-ray scans.

To access and modify DICOM tags programmatically, this Skill parses the medical imaging datasets to retrieve, alter, and manage metadata attributes associated with CT, MRI, and X-ray files.

To handle compressed DICOM pixel data, you need dependencies like pylibjpeg, pylibjpeg-libjpeg, pylibjpeg-openjpeg, and python-gdcm, which this Skill uses to decode and process medical imaging datasets.