[![License](https://img.shields.io/badge/License-EPL%202.0-blue.svg)](https://opensource.org/licenses/EPL-2.0) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) ![Maven Build](https://github.com/nroduit/weasis/workflows/Build/badge.svg) ![Github](https://img.shields.io/github/downloads/nroduit/weasis/total?classes=inline "Github release downloads")

[![Sonar](https://sonarcloud.io/api/project_badges/measure?project=org.weasis%3Aweasis-framework&metric=ncloc)](https://sonarcloud.io/component_measures?id=org.weasis%3Aweasis-framework) [![Sonar](https://sonarcloud.io/api/project_badges/measure?project=org.weasis%3Aweasis-framework&metric=reliability_rating)](https://sonarcloud.io/component_measures?id=org.weasis%3Aweasis-framework) [![Sonar](https://sonarcloud.io/api/project_badges/measure?project=org.weasis%3Aweasis-framework&metric=sqale_rating)](https://sonarcloud.io/component_measures?id=org.weasis%3Aweasis-framework) [![Sonar](https://sonarcloud.io/api/project_badges/measure?project=org.weasis%3Aweasis-framework&metric=security_rating)](https://sonarcloud.io/component_measures?id=org.weasis%3Aweasis-framework) [![Sonar](https://sonarcloud.io/api/project_badges/measure?project=org.weasis%3Aweasis-framework&metric=alert_status)](https://sonarcloud.io/dashboard?id=org.weasis%3Aweasis-framework)

## Table of Contents
- [About Weasis](#about-weasis)
- [Getting Started](#getting-started)
- [Release History](#release-history)
- [Build Weasis](#build-weasis)
- [General Features](#general-features)
- [Connectivity & Interoperability](#connectivity--interoperability)
- [Viewer Features](#viewer-features-see-also-tutorials)
- [Security & Quality](#security--quality)
- [Community and Support](#community-and-support)
- [License](#license)

## About Weasis

**Weasis** is a powerful, multifunctional, and open-source DICOM viewer designed for both standalone and web-based use. It excels in medical image visualization and is widely used by healthcare professionals and research institutions. Engineered for seamless integration with PACS and DICOM workflows, Weasis offers a reliable solution for modern medical imaging needs — from routine reading to AI-assisted review and quantitative imaging.

<img src='./weasis.jpg' width='100%' alt='Weasis DICOM viewer'>.

## Getting Started
* [General information](https://nroduit.github.io)
* [Getting Started](https://nroduit.github.io/en/getting-started)
* [Download binary releases](https://nroduit.github.io/en/getting-started/download-dicom-viewer)
* [Live Demo with different datasets](https://nroduit.github.io/en/demo)

## Release History
See [CHANGELOG](CHANGELOG.md)

## Build Weasis
See [How to build Weasis](https://nroduit.github.io/en/getting-started/building-weasis)

## General Features
* Open source DICOM viewer under EPL 2 or Apache 2 license
* Flexible integration with PACS, VNA, RIS, HIS, or EHR  (see [integration documentation](https://nroduit.github.io/en/basics/customize/integration/))
* [Desktop distributions](https://nroduit.github.io/en/getting-started/download-dicom-viewer/) (Windows, macOS, and Linux)
* Web access through the [weasis protocol](https://nroduit.github.io/en/getting-started/weasis-protocol)
* [Responsive user interface](https://nroduit.github.io/en/tutorials/theme/index.html#how-to-scale-the-user-interface) working well on high-DPI screens
* [Multi-language support](https://nroduit.github.io/en/getting-started/translating/) (20+ languages)
* [Configuration of preferences](https://nroduit.github.io/en/basics/customize/preferences/) on server-side and client-side, multi-level overrides (default → workstation → user)
* [API for building custom plug-ins](https://nroduit.github.io/en/basics/customize/build-plugins/) via the Weasis plug-in archetype
* [Embedded DICOM viewer in CD/DVD](https://nroduit.github.io/en/tutorials/dicom-export/index.html#cddvd-image) or other portable media
* Dicomizer module to convert standard images, videos, PDFs and STL meshes into DICOM files
* [AI-assisted and quantitative imaging workflows](https://nroduit.github.io/en/tutorials/dicom-artificial-intelligence/)

## Connectivity & Interoperability
Weasis supports every common DICOM transport and authentication standard, fitting into existing clinical infrastructure — PACS, VNA, EHR, RIS, and HIS — in two complementary ways:

* **Server-side, via a gateway** such as [ViewerHub](https://nroduit.github.io/en/viewer-hub/) — recommended for clean, centralized integration: the gateway brokers PACS / DICOMweb access, handles authentication and manifest generation, and exposes a single endpoint to the viewer.
* **Client-side**, by configuring **DICOM nodes and DICOMweb sources** directly in Weasis — useful for standalone workstations, smaller sites, or when no gateway is available.
* **Classic DIMSE** — Query/Retrieve (C-FIND, C-GET, C-MOVE) and Store (C-STORE).
* **DICOMweb** — [QIDO-RS, WADO-RS and STOW-RS](https://nroduit.github.io/en/tutorials/dicomweb-config) over HTTPS, configurable per source.
* **WADO-URI** — for legacy PACS servers and the [Weasis manifest](https://nroduit.github.io/en/basics/customize/integration/index.html#build-an-xml-manifest) flow.
* **`weasis://` protocol** — single-click launch from browsers, EHR and RIS portals.
* **Authentication** — Basic auth, OAuth 2.0 and **OpenID Connect** (Authorization Code with PKCE and loopback redirect, RFC 8252) — works against Keycloak, Google Cloud Healthcare and any compliant OIDC provider.
* **Send / Export** — store to a PACS or DICOMweb server (C-STORE or STOW-RS), or export locally as DICOMDIR ZIP, ISO with the Weasis CD viewer embedded, JPEG, PNG, TIFF, AVI / MP4.
* **Integration hooks** — argument-driven launch, manifest-based study loading, downloadable manifests with WADO; documented contracts for EHR / RIS / HIS integration.

## Viewer Features (see also [Tutorials](https://nroduit.github.io/en/tutorials/))

* **Data type support**
  * Display every common DICOM file including multi-frame, **Enhanced** (CT / MR / US Volume), MPEG-2, MPEG-4, MIME Encapsulation, DOC, **[SR](https://nroduit.github.io/en/tutorials/dicom-sr/)**, **[PR](https://nroduit.github.io/en/tutorials/build-ko-pr/)**, **[KOS](https://nroduit.github.io/en/tutorials/build-ko-pr/)**, **[SEG](https://nroduit.github.io/en/tutorials/dicom-segmentation/)**, [AU](https://nroduit.github.io/en/tutorials/dicom-audio/), **[RT](https://nroduit.github.io/en/tutorials/dicom-rt/)**, **[ECG](https://nroduit.github.io/en/tutorials/dicom-ecg/)** and **[Parametric Map](https://nroduit.github.io/en/tutorials/dicom-artificial-intelligence/index.html#dicom-parametric-map-pmap)** (float / double pixels)
  * Modern codecs: JPEG (baseline, extended, lossless), JPEG-LS, JPEG 2000, **JPEG-XL**, RLE, Deflated Explicit VR Little Endian
  * [Import](https://nroduit.github.io/en/tutorials/dicom-import/) and [export](https://nroduit.github.io/en/tutorials/dicom-export/) DICOM CD/DVD with DICOMDIR
  * [Import](https://nroduit.github.io/en/tutorials/dicom-import/) and [export](https://nroduit.github.io/en/tutorials/dicom-export/) DICOM ZIP files
  * Viewer for common image formats (TIFF, BMP, GIF, JPEG, PNG, RAS, HDR, PNM)

* **Exporting data**
  * [Export DICOM files locally](https://nroduit.github.io/en/tutorials/dicom-export/index.html#exporting) with several options (DICOMDIR, ZIP, ISO image with Weasis embedded, TIFF, JPEG, PNG…)
  * [Send DICOM files](https://nroduit.github.io/en/tutorials/dicom-export/index.html#exporting) to a remote PACS or DICOMweb server (C-STORE or STOW-RS)
  * Save measurements and annotations as [DICOM Presentation States](https://nroduit.github.io/en/tutorials/build-ko-pr/) or XML

* **Viewing and image rendering**
  * Multi-monitor support with **[per-monitor calibration](https://nroduit.github.io/en/tutorials/zoom/index.html#real-world-size-display)**, HiDPI, full-screen mode
  * Image manipulation with mouse buttons (pan, zoom, windowing, rotation, scroll, crosshair) and **[customizable keyboard shortcuts](https://nroduit.github.io/en/basics/shortcuts/)**
  * [DICOM Modality LUTs, VOI LUTs, LUT Shapes, and Presentation LUTs](https://nroduit.github.io/en/tutorials/lut/) (including non-linear)
  * [DICOM Presentation States (GSPS)](https://nroduit.github.io/en/tutorials/build-ko-pr/) — applied with graphics rendered as overlays
  * [DICOM Overlays, Shutters and Pixel Padding](https://nroduit.github.io/en/tutorials/dicom-2d-viewer/index.html#display)
  * **Lossy compression indicator** in the [information layer](https://nroduit.github.io/en/tutorials/dicom-2d-viewer/index.html#display) so the user knows the source quality, messages when geometry issues are detected (inconsistent pixel spacing, slice spacing, or orientation across the series)
  * **[Per-view synchronization](https://nroduit.github.io/en/tutorials/synch-view/)** with explicit overrides and **FrameOfReferenceUID-aware** grouping (orphan views are excluded from auto-sync to prevent comparing unrelated anatomy)

* **Advanced imaging**
  * **[Oblique Multi-Planar Reconstruction (MPR)](https://nroduit.github.io/en/tutorials/mpr/)** with **gantry-tilt correction** (backward mapping + trilinear interpolation) and 3D matrix transformations for non-standard patient positioning
  * **[Curved MPR (CPR)](https://nroduit.github.io/en/tutorials/mpr-curved/)**: trace a curve on the axial plane — typically the dental arch on a cone-beam CT — to build a panoramic view and cross-sectional slices
  * **[Maximum Intensity Projection (MIP / MinIP / Mean IP)](https://nroduit.github.io/en/tutorials/mip/)** available in the 2D, MPR and 3D views
  * **[3D Volume Rendering](https://nroduit.github.io/en/tutorials/dicom-3d-viewer/)** with presets, custom Volume LUTs, and [segmentation modes](https://nroduit.github.io/en/tutorials/dicom-segmentation/index.html#segmentation-overlay-in-the-3d-volume-renderer) including **masks** that keep or remove the voxels inside the segmentation
  * **[DICOM Segmentation (SEG)](https://nroduit.github.io/en/tutorials/dicom-segmentation/)** overlay in 2D, MPR and 3D, with per-region visibility, color, opacity and statistics
  * **[PET/CT fusion](https://nroduit.github.io/en/tutorials/fusion/)**: overlay a PET or SPECT series on its CT / MR base, with SUV display window and color scale
  * **[4D / multi-phase series](https://nroduit.github.io/en/tutorials/dicom-explorer/index.html#4d-splitting)**: automatic dialog to split a multi-phase series into per-phase sub-series for MPR, MIP and VR
  * Cross-lines, [3D cursor](https://nroduit.github.io/en/tutorials/cursor-3d/)
  * [Persistent magnifier glass](https://nroduit.github.io/en/tutorials/zoom/)
  * [Layouts](https://nroduit.github.io/en/tutorials/docking/) for comparing series, studies or modalities side-by-side

* **Measurement and annotation tools**
  * [Length, area, angle (incl. Cobb), perpendicular, parallel and free-shape](https://nroduit.github.io/en/tutorials/draw-measure/index.html#measurement-tools)
  * [Region statistics of pixels](https://nroduit.github.io/en/tutorials/draw-measure/index.html#selected-measurement) (Min, Max, Mean, StDev, Skewness, Kurtosis, Entropy)
  * [Histogram](https://nroduit.github.io/en/tutorials/histogram/) of modality values
  * SUV measurement (PET / nuclear medicine), also on a [fused PET/CT view](https://nroduit.github.io/en/tutorials/fusion/index.html#suv)
  * [Volume and voxel count of segmented regions](https://nroduit.github.io/en/tutorials/dicom-segmentation/index.html#region-info)
  * [Pixel-info inspector](https://nroduit.github.io/en/tutorials/dicom-2d-viewer/index.html#display) (raw value, modality value, presentation value)

* **Specific viewers**
  * **[DICOM ECG](https://nroduit.github.io/en/tutorials/dicom-ecg/)**: display all the DICOM waveforms and allow measurements
  * **[DICOM SR](https://nroduit.github.io/en/tutorials/dicom-sr/)**: structured report viewer with hyperlinks to images and associated graphics
  * **[DICOM AU](https://nroduit.github.io/en/tutorials/dicom-audio/)**: audio player (allow to export to WAV files)
  * **[DICOM RT](https://nroduit.github.io/en/tutorials/dicom-rt/)**: structure-set, dose distribution and DVH viewer

* **Other tools**
  * [Printing views](https://nroduit.github.io/en/tutorials/print/) to DICOM and system printers
  * Apply and Create [DICOM Key Object Selection](https://nroduit.github.io/en/tutorials/build-ko-pr/) by selecting images with the star button
  * [Display and search across all DICOM attributes](https://nroduit.github.io/en/tutorials/tags/)
  * **[Acquire / Dicomizer](https://nroduit.github.io/en/tutorials/dicomizer/)**: capture or import non-DICOM media (images, videos, PDFs, STL meshes) and convert into DICOM, with video size validation and per-modality presets

## Security & Quality

* **Authentication & transport** — OAuth 2.0 / OpenID Connect for resource-server access; HTTPS for transport; code-signed installers.
* **Supply chain** — SBOM-tracked dependencies, continuous CVE monitoring.
* **Test coverage** — unit and integration tests pin the most sensitive parts (DICOM decoding, identity model, pixel/LUT pipeline, measurement statistics, anonymisation, authentication, view synchronisation).
* **Static analysis** — every build is scanned by [SonarCloud](https://sonarcloud.io/dashboard?id=org.weasis%3Aweasis-framework) for reliability, maintainability and security ratings, with quality-gate status enforced on the main branch (see badges at the top).
* **Upstream libraries** — [`weasis-core-img`](https://github.com/nroduit/weasis-core-img) and [`weasis-dicom-tools`](https://github.com/nroduit/weasis-dicom-tools) maintain their own ISO 14971-style risk-coverage matrices, cited from this repository's verification index.

## Community and Support
Weasis encourages community participation. Whether you're reporting bugs, suggesting features, or seeking help, you can connect with others here:
* [GitHub Issues](https://github.com/nroduit/Weasis/issues)
* Forum: [Google group](https://groups.google.com/forum/#!forum/dcm4che) or [GitHub Discussions](https://github.com/nroduit/Weasis/discussions)
* [Frequently Asked Questions](https://nroduit.github.io/en/faq/)
* [Contributing guide](CONTRIBUTING.md)

## License
Weasis is dual-licensed under the [EPL 2.0](https://opensource.org/licenses/EPL-2.0) and [Apache 2.0](https://opensource.org/licenses/Apache-2.0).