# pydicom/pydicom

Read, modify and write DICOM files with python code

Repository: https://github.com/pydicom/pydicom
Canonical: https://ross.abutalabs.com/products/pydicom
Homepage: https://pydicom.github.io/pydicom/dev
Language: Python
License: NOASSERTION
License Family: other
Topics: dicom, pydicom, python
Last push: 2026-08-03T17:17:51+00:00

## Health v2 (maintenance only)
Score: 89/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 95, release rhythm 75, longevity 100
- inputs: {"age_days": 4689, "days_push": 30, "days_rel": 166, "gap_med": 13, "n_releases_24m": 4}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2197, forks 546 (observed 2026-08-28T04:06:25.268762+00:00)

## What it is
pydicom is a pure Python library for reading, modifying, and writing DICOM medical imaging files and File-sets in a pythonic way. It optionally converts compressed and uncompressed Pixel Data to NumPy ndarrays and back.

## Use cases
- read and parse DICOM files in python
- modify DICOM metadata like patient name and save the file
- convert DICOM pixel data to a numpy array
- work with DICOMDIR and DICOM File-sets
- extract medical imaging data for machine learning pipelines
- write DICOM datasets from scratch in python

## When to choose
- you need general-purpose DICOM dataset I/O in Python without heavy dependencies
- you want to inspect or edit DICOM tags and metadata programmatically
- you need pixel data as NumPy arrays for analysis or ML
- you want a pure Python library that runs anywhere Python runs

## When to avoid
- you need DICOM networking or SOP class services (use pynetdicom instead)
- you need turnkey anonymization workflows (use deid instead)
- you need a full medical imaging viewer or PACS application

## Facets
- artifact type: library
- maturity: stable
- function: parser, serialization, image-processing, file-system
- domain: healthcare, image-processing, files, developer-tools
- platform: python, cross-platform
- tags: dicom, medical-imaging, pixel-data, numpy, pure-python

## Member repositories
- pydicom/pydicom (main) score 89

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:25.268762+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:47:10.246854+00:00, confidence not recorded.
  - readme: https://github.com/pydicom/pydicom (fetched 2026-08-28T04:06:25.268762+00:00, sha ce2dd28eb671)
  - homepage: https://pydicom.github.io/pydicom/dev (fetched 2026-08-29T10:27:26.786559+00:00, sha 73b8c167610f)
  - registry_pypi: https://pypi.org/pypi/pydicom/json (fetched 2026-08-29T10:27:26.789138+00:00, sha 3181028614f0)
- Data as of 2026-08-30T08:39:29.467469+00:00.