[![NPM version][npm-version-image]][npm-url] [![MIT License][license-image]][license-url] ![This project is using Percy.io for visual regression testing.][percy-image]
<!-- [![NPM downloads][npm-downloads-image]][npm-url] --> <!-- [![Pulls][docker-pulls-img]][docker-image-url] --> <!-- [](https://app.fossa.io/projects/git%2Bgithub.com%2FOHIF%2FViewers?ref=badge_shield) --> <!-- [![Netlify Status][netlify-image]][netlify-url] --> <!-- [![CircleCI][circleci-image]][circleci-url] --> <!-- [![codecov][codecov-image]][codecov-url] --> <!-- [](#contributors) --> <!-- prettier-ignore-end --><img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-measurements.webp?raw=true" alt="Measurement tracking" width="350"/> | Measurement Tracking | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-segmentation.webp?raw=true" alt="Segmentations" width="350"/> | Labelmap Segmentations | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-ptct.webp?raw=true" alt="Hanging Protocols" width="350"/> | Fusion and Custom Hanging protocols | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-volume-rendering.webp?raw=true" alt="Volume Rendering" width="350"/> | Volume Rendering | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-pdf.webp?raw=true" alt="PDF" width="350"/> | Demo | |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-rtstruct.webp?raw=true" alt="RTSTRUCT" width="350"/> | RT STRUCT | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-4d.webp?raw=true" alt="4D" width="350"/> | 4D | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/demo-video.webp?raw=true" alt="VIDEO" width="350"/> | Video | Demo |
<img src="https://github.com/OHIF/Viewers/blob/master/platform/docs/docs/assets/img/microscopy.webp?raw=true" alt="microscopy" width="350"/> | Slide Microscopy | Demo |
The OHIF Viewer can retrieve and load images from most sources and formats; render sets in 2D, 3D, and reconstructed representations; allows for the manipulation, annotation, and serialization of observations; supports internationalization, OpenID Connect, offline use, hotkeys, and many more features.
Almost everything offers some degree of customization and configuration. If it doesn't support something you need, we accept pull requests and have an ever improving Extension System.
The OHIF Viewer is a collaborative effort that has served as the basis for many active, production, and FDA Cleared medical imaging viewers. It benefits from our extensive community's collective experience, and from the sponsored contributions of individuals, research groups, and commercial organizations.
After more than 8-years of integrating with many companies and organizations, The OHIF Viewer has been rebuilt from the ground up to better address the varying workflow and configuration needs of its many users. All of the Viewer's core features are built using it's own extension system. The same extensibility that allows us to offer:
Can be leveraged by you to customize the viewer for your workflow, and to add any new functionality you may need (and wish to maintain privately without forking).
For commercial support, academic collaborations, and answers to common questions; please use Get Support to contact us.
master
branch - The latest dev (beta) releasemaster
- The latest dev releaseThis is typically where the latest development happens. Code that is in the master branch has passed code reviews and automated tests, but it may not be deemed ready for production. This branch usually contains the most recent changes and features being worked on by the development team. It's often the starting point for creating feature branches (where new features are developed) and hotfix branches (for urgent fixes).
Each package is tagged with beta version numbers, and published to npm such as @ohif/ui@3.6.0-beta.1
release/*
branches - The latest stable releasesOnce the master
branch code reaches a stable, release-ready state, we conduct a comprehensive code review and QA testing. Upon approval, we create a new release branch from master
. These branches represent the latest stable version considered ready for production.
For example, release/3.5
is the branch for version 3.5.0, and release/3.6
is for version 3.6.0. After each release, we wait a few days to ensure no critical bugs. If any are found, we fix them in the release branch and create a new release with a minor version bump, e.g., 3.5.1 in the release/3.5
branch.
Each package is tagged with version numbers and published to npm, such as @ohif/ui@3.5.0
. Note that master
is always ahead of the release
branch. We publish docker builds for both beta and stable releases.
Here is a schematic representation of our development workflow:
yarn config set workspaces-experimental true
git clone https://github.com/YOUR-USERNAME/Viewers.git
remote
named upstream
git remote add upstream https://github.com/OHIF/Viewers.git
yarn install
to restore dependencies and link projectsFrom this repository's root directory:
# Enable Yarn Workspaces yarn config set workspaces-experimental true # Restore dependencies yarn install
These commands are available from the root directory. Each project directory
also supports a number of commands that can be found in their respective
README.md
and package.json
files.
Yarn Commands | Description |
---|---|
Develop | |
dev or start | Default development experience for Viewer |
test:unit | Jest multi-project test runner; overall coverage |
Deploy | |
build * | Builds production output for our PWA Viewer |
* - For more information on our different builds, check out our [Deploy Docs][deployment-docs]
The OHIF Medical Image Viewing Platform is maintained as a
[monorepo
][monorepo]. This means that this repository, instead of containing a
single project, contains many projects. If you explore our project structure,
you'll see the following:
. ├── extensions # │ ├── _example # Skeleton of example extension │ ├── default # basic set of useful functionalities (datasources, panels, etc) │ ├── cornerstone # image rendering and tools w/ Cornerstone3D │ ├── cornerstone-dicom-sr # DICOM Structured Report rendering and export │ ├── cornerstone-dicom-sr # DICOM Structured Report rendering and export │ ├── cornerstone-dicom-seg # DICOM Segmentation rendering and export │ ├── cornerstone-dicom-rt # DICOM RTSTRUCT rendering │ ├── cornerstone-microscopy # Whole Slide Microscopy rendering │ ├── dicom-pdf # PDF rendering │ ├── dicom-video # DICOM RESTful Services │ ├── measurement-tracking # Longitudinal measurement tracking │ ├── tmtv # Total Metabolic Tumor Volume (TMTV) calculation | │ ├── modes # │ ├── _example # Skeleton of example mode │ ├── basic-dev-mode # Basic development mode │ ├── longitudinal # Longitudinal mode (measurement tracking) │ ├── tmtv # Total Metabolic Tumor Volume (TMTV) calculation mode │ └── microscopy # Whole Slide Microscopy mode │ ├── platform # │ ├── core # Business Logic │ ├── i18n # Internationalization Support │ ├── ui # React component library │ ├── docs # Documentation │ └── viewer # Connects platform and extension projects │ ├── ... # misc. shared configuration ├── lerna.json # MonoRepo (Lerna) settings ├── package.json # Shared devDependencies and commands └── README.md # This file
To acknowledge the OHIF Viewer in an academic publication, please cite
Open Health Imaging Foundation Viewer: An Extensible Open-Source Framework for Building Web-Based Imaging Applications to Support Cancer Research
Erik Ziegler, Trinity Urban, Danny Brown, James Petts, Steve D. Pieper, Rob Lewis, Chris Hafey, and Gordon J. Harris
JCO Clinical Cancer Informatics, no. 4 (2020), 336-345, DOI: 10.1200/CCI.19.00131
Open-Access on Pubmed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259879/
or, for v1, please cite:
LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials
Trinity Urban, Erik Ziegler, Rob Lewis, Chris Hafey, Cheryl Sadow, Annick D. Van den Abbeele and Gordon J. Harris
Cancer Research, November 1 2017 (77) (21) e119-e122 DOI: 10.1158/0008-5472.CAN-17-0334
Note: If you use or find this repository helpful, please take the time to star this repository on GitHub. This is an easy way for us to assess adoption and it can help us obtain future funding for the project.
This work is supported primarily by the National Institutes of Health, National Cancer Institute, Informatics Technology for Cancer Research (ITCR) program, under a grant to Dr. Gordon Harris at Massachusetts General Hospital (U24 CA199460).
NCI Imaging Data Commons (IDC) project supported the development of new features and bug fixes marked with "IDC:priority", "IDC:candidate" or "IDC:collaboration". NCI Imaging Data Commons is supported by contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI. IDC Viewer is a customized version of the OHIF Viewer.
This project is tested with BrowserStack. Thank you for supporting open-source!
MIT © OHIF
<!-- Links --> <!-- prettier-ignore-start --> <!-- Badges -->[circleci-image]:
一键生成PPT和Word,让学习生活更轻松
讯飞智文是一个利用 AI 技术的项目,能够帮助用户生成 PPT 以及各类文档。无论是商业领域的市场分析报告、年度目标制定,还是学生群体的职业生涯规划、实习避坑指南,亦或是活动策划、旅游攻略等内容,它都能提供支持,帮助用户精准表达,轻松呈现各种信息。
深度推理能力全新升级,全面对标OpenAI o1
科大讯飞的星火大模型,支持语言理解、知识问答和文本创作等多功能,适用于多种文件和业务场景,提升办公和日常生活的效率。讯飞星火是一个提供丰富智能服务的平台,涵盖科技资讯、图像创作、写作辅助、编程解答、科研文献解读 等功能,能为不同需求的用户提供便捷高效的帮助,助力用户轻松获取信息、解决问题,满足多样化使用场景。
一种基于大语言模型的高效单流解耦语音令牌文本到语音合成模型
Spark-TTS 是一个基于 PyTorch 的开源文本到语音合成项目,由多个知名机构联合参与。该项目提供了高效的 LLM(大语言模型)驱动的语音合成方案,支持语音克隆和语音创建功能,可通过命令行界面(CLI)和 Web UI 两种方式使用。用户可以根据需求调整语音的性别、音高、速度等参数,生成高质量的语音。该项目适用于多种场景,如有声读物制作、智能语音助手开发等。
字节跳动发布的AI编程神器IDE
Trae是一种自适应的集成开发环境(IDE),通过自 动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。
AI助力,做PPT更简单!
咔片是一款轻量化在线演示设计工具,借助 AI 技术,实现从内容生成到智能设计的一站式 PPT 制作服务。支持多种文档格式导入生成 PPT,提供海量模板、智能美化、素材替换等功能,适用于销售、教师、学生等各类人群,能高效制作出高品质 PPT,满足不同场景演示需求。
选题、配图、成文,一站式创作,让内容运营更高效
讯飞绘文,一个AI集成平台,支持写作、选题、配图、排版和发布。高效生成适用于各类媒体的定制内容,加速品牌传播,提升内容营销效果。
专业的AI公文写作平台,公文写作神器
AI 材料星,专业的 AI 公文写作辅助平台,为体制内工作人员提供高效的公文写作解决方案。拥有海量公文文库、9 大核心 AI 功能,支 持 30 + 文稿类型生成,助力快速完成领导讲话、工作总结、述职报告等材料,提升办公效率,是体制打工人的得力写作神器。
OpenAI Agents SDK,助力开发者便捷使用 OpenAI 相关功能。
openai-agents-python 是 OpenAI 推出的一款强大 Python SDK,它为开发者提供了与 OpenAI 模型交互的高效工具,支持工具调用、结果处理、追踪等功能,涵盖多种应用场景,如研究助手、财务研究等,能显著提升开发效率,让开发者更轻松地利用 OpenAI 的技术优势。
高分辨率纹理 3D 资产生成
Hunyuan3D-2 是腾讯开发的用于 3D 资产生成的强大工具,支持从文本描述、单张图片或多视角图片生成 3D 模型,具备快速形状生成能力,可生成带纹理的高质量 3D 模型,适用于多个领域,为 3D 创作提供了高效解决方案。
一个具备存储、管理和客户端操作等多种功能的分布式文件系统相关项目。
3FS 是一个功能强大的分布式文件系统项目,涵盖了存储引擎、元数据管理、客户端工具等多个模块。它支持多种文件操作,如创建文件和目录、设置布局等,同时具备高效的事件循环、节点选择和协程池管理等特性。适用于需要大规模数据存储和管理的场景,能够提高系统的性能和可靠性,是分布式存储领域的优质解决方案。
最新AI工具、AI资讯
独家AI资源、AI项目落地
微信扫一扫关注公众号