pydicom

Pydicom

Overview

Pydicom is a pure Python package for working with DICOM files, the standard format for medical imaging data. This skill provides guidance on reading, writing, and manipulating DICOM files, including working with pixel data, metadata, and various compression formats.

When to Use This Skill

Use this skill when working with:

• Medical imaging files (CT, MRI, X-ray, ultrasound, PET, etc.)
• DICOM datasets requiring metadata extraction or modification
• Pixel data extraction and image processing from medical scans
• DICOM anonymization for research or data sharing
• Converting DICOM files to standard image formats
• Compressed DICOM data requiring decompression
• DICOM sequences and structured reports
• Multi-slice volume reconstruction
• PACS (Picture Archiving and Communication System) integration

Installation

Install pydicom and common dependencies:

uv pip install pydicom
uv pip install pillow  # For image format conversion
uv pip install numpy   # For pixel array manipulation
uv pip install matplotlib  # For visualization

For handling compressed DICOM files, additional packages may be needed:

uv pip install pylibjpeg pylibjpeg-libjpeg pylibjpeg-openjpeg  # JPEG compression
uv pip install python-gdcm  # Alternative compression handler

Core Workflows

Reading DICOM Files

Read a DICOM file using pydicom.dcmread():

import pydicom

# Read a DICOM file
ds = pydicom.dcmread('path/to/file.dcm')

# Access metadata
print(f"Patient Name: {ds.PatientName}")
print(f"Study Date: {ds.StudyDate}")
print(f"Modality: {ds.Modality}")

# Display all elements
print(ds)

Key points:

• dcmread() returns a Dataset object
• Access data elements using attribute notation (e.g., ds.PatientName) or tag notation (e.g., ds[0x0010, 0x0010])
• Use ds.file_meta to access file metadata like Transfer Syntax UID
• Handle missing attributes with getattr(ds, 'AttributeName', default_value) or hasattr(ds, 'AttributeName')