# Slicer/Slicer

Multi-platform, free open source software for visualization and image computing.

Repository: https://github.com/Slicer/Slicer
Canonical: https://ross.abutalabs.com/products/slicer
Homepage: https://www.slicer.org
Language: C++
License: NOASSERTION
License Family: other
Topics: medical-imaging, vtk, itk, python, qt, image-processing, national-institutes-of-health, medical-image-computing, neuroimaging, tractography, image-guided-therapy, registration, segmentation, 3d-printing, nih, 3d-slicer, tcia-dac, kitware, c-plus-plus, computed-tomography
Last push: 2026-08-26T04:37:55+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 2365, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- 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 2595, forks 776 (observed 2026-08-28T04:07:03.154219+00:00)

## What it is
3D Slicer is a free, open-source desktop platform for visualization, processing, segmentation, registration, and analysis of medical and biomedical 3D images and meshes. It also serves as a development platform for building custom image-computing solutions and image-guided procedure navigation via an extensible Python/C++ module system.

## Use cases
- segment medical images like MRI and CT scans
- visualize and analyze DICOM volumes in 3D
- run tractography on diffusion MRI data
- plan surgical or image-guided procedures
- prepare segmentation models for 3D printing
- deploy deep learning models for automatic anatomy segmentation
- register multiple medical image volumes
- build custom medical imaging research applications in Python

## When to choose
- you need a comprehensive, free medical image computing workstation across Windows, Linux, and macOS
- you want an extensible research platform with Python scripting and a large extension ecosystem
- you need clinically oriented tools for segmentation, registration, navigation, or quantitative imaging

## When to avoid
- you need a lightweight command-line batch pipeline rather than an interactive GUI application
- your imaging domain is non-medical general-purpose photo editing
- you require a small, embeddable library instead of a full desktop application

## Facets
- artifact type: application
- maturity: stable
- function: image-processing, computer-vision, machine-learning, data-visualization, gui, plugin-system, sdk
- domain: healthcare, image-processing, computer-vision, machine-learning, simulation, cross-platform
- platform: windows, cpp, python
- tags: medical-imaging, dicom, segmentation, registration, tractography, neuroimaging, image-guided-therapy, 3d-printing, vtk, itk, qt, linux, macos, desktop

## Member repositories
- Slicer/Slicer (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:03.154219+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 2026-08-30T02:22:15.005048+00:00, confidence not recorded.
  - readme: https://github.com/Slicer/Slicer (fetched 2026-08-28T04:07:03.154219+00:00, sha c53e90da7451)
  - homepage: https://www.slicer.org (fetched 2026-08-29T10:04:29.788631+00:00, sha c10fbfa38188)
  - site_page: https://www.slicer.org/wiki/Documentation/Nightly/Modules/DeepInfer (fetched 2026-08-29T10:04:29.793558+00:00, sha 553627899522)
  - site_page: https://www.slicer.org/wiki/Documentation/Nightly/Training (fetched 2026-08-29T10:04:29.795407+00:00, sha b682cd684d4b)
  - site_page: https://www.slicer.org/wiki/Documentation/Nightly/Modules/UKFTractography (fetched 2026-08-29T10:04:29.791535+00:00, sha fd77e450b1e6)
  - site_page: https://www.slicer.org/wiki/Main_Page/SlicerCommunity (fetched 2026-08-29T10:04:29.797657+00:00, sha 93b7358bb8e9)
- Data as of 2026-08-30T08:39:29.467469+00:00.