List of the Top 10 DICOM Viewers for Linux in 2025

3D Slicer is a freely available open-source software designed for the visualization, processing, segmentation, registration, and analysis of various medical and 3D images as well as meshes. It facilitates the planning and navigation of image-guided procedures. As a desktop application, 3D Slicer addresses intricate challenges in image computing, especially in clinical and biomedical scenarios. Moreover, it functions as a flexible development platform, enabling the rapid creation and deployment of customized solutions for both research and commercial projects. Supported by a robust community of skilled users and developers, 3D Slicer continually advances the field of medical computing. The software is distributed under a BSD-style license, which means there are no restrictions on its use in academic or commercial applications. However, it is important to emphasize that 3D Slicer does not have FDA approval, placing the responsibility on users to comply with applicable regulations. This collaborative ecosystem not only improves the software but also fosters innovation within medical imaging and analysis industries. Additionally, the ongoing contributions from the community help to refine the tools and techniques available, ensuring that 3D Slicer remains at the forefront of technological advancements.

The OHIF Viewer, provided by the Open Health Imaging Foundation, is an open-source web-based platform that focuses on medical imaging and offers a solid foundation for developing complex imaging applications. It is engineered to efficiently load extensive radiology studies by pre-fetching crucial metadata and streaming pixel data as necessary. With the incorporation of Cornerstone3D, it adeptly decodes, renders, and annotates medical images. Users enjoy seamless integration with DICOMWeb-compliant image archives and a data source API that facilitates connections with proprietary API formats. The viewer's plugin architecture supports the creation of tailored workflow modes that leverage existing core features. Moreover, its user interface, developed with React.js and Tailwind CSS, not only presents an attractive design but is also designed for extensibility, featuring a library of reusable UI components that improve usability and customization. In addition, this collection of attributes makes the OHIF Viewer a highly adaptable asset in the realm of medical imaging, catering to a wide range of user needs and applications.

Weasis is a free, open-source DICOM viewer that is designed for both standalone applications and web-based platforms, featuring a modular architecture. It is widely utilized in various healthcare settings, including hospitals, health networks, multicenter research initiatives, and even for individual patients. As a cross-platform tool, Weasis integrates smoothly with systems like PACS, RIS, HIS, or EHR, enhancing its versatility. The viewer leverages the OpenCV library to provide high-performance rendering and outstanding quality in medical imaging. From version 4 onward, Weasis presents a user-friendly interface that adapts to different operating systems, thereby improving the viewing experience on high-resolution screens. Notably, it supports a wide range of DICOM file formats, such as multi-frame, enhanced, MPEG-2, and MPEG-4, among others. Users can conveniently import DICOM files utilizing DICOM Query/Retrieve (C-GET, C-MOVE, WADO-URI) and DICOMWeb (QUERY and RETRIEVE) protocols, as well as manage DICOM data stored on CDs or DVDs with DICOMDIR. Moreover, Weasis is committed to ongoing improvement, continually refining its features and performance based on user input. This dedication to adaptability ensures that it remains relevant and effective in the ever-evolving landscape of medical imaging technology.

PostDICOM serves as a robust, cloud-based platform for DICOM file viewing and medical imaging management, allowing users to effortlessly view, store, and share DICOM files through any modern web browser. This adaptable tool supports a wide variety of imaging techniques, including CT, MRI, ultrasound, PET, and X-ray, granting users the ability to remotely access their imaging studies without the need for any software installation. Featuring a comprehensive set of advanced capabilities, PostDICOM facilitates both 2D and 3D image visualization, offers multiplanar reconstruction (MPR), and supports image fusion functionalities. Users can annotate images, conduct measurements, and adjust brightness, contrast, and window levels to optimize their analysis. The platform also includes a management system specifically designed for educational files, allowing the creation and organization of teaching cases, which proves invaluable for learning purposes. Additionally, its collaborative workspaces enable healthcare professionals to seamlessly collaborate while managing user access to streamline their workflow. Moreover, PostDICOM places a strong emphasis on data protection and confidentiality by providing tools for patient data anonymization and ensuring compliance with HIPAA regulations. This combination of extensive features and regulatory adherence underscores its significance in contemporary medical imaging practices, making it an indispensable resource for professionals in the field. Ultimately, its user-friendly interface and comprehensive functionality make it a top choice for medical imaging solutions.

Mango Viewer is a powerful graphical user interface designed specifically for the analysis of medical images, accommodating a wide range of file formats, including DICOM, NIfTI, and ANALYZE. This application provides an extensive array of tools for examining and interpreting medical imaging data, featuring multi-planar viewing options such as axial, sagittal, and coronal views, in addition to sophisticated surface rendering capabilities and functions for defining and analyzing regions of interest. The user-friendly interface of Mango facilitates scripting and batch processing, making repetitive tasks much easier for users. Moreover, it includes advanced features like image overlay, image fusion, and visualization of 4D data, along with dynamic contrast-enhanced imaging capabilities. Users can leverage ROI tools to extract important statistical information, such as volume, mean, and standard deviation, and they can create ROIs either manually or through automated methods. Furthermore, Mango’s proficiency in managing multiple images proves beneficial for comparative studies, and its functionality is enhanced by plugins that cater to brain mapping, tractography, and perfusion analysis. Notably, this adaptable software is platform-independent, ensuring users can access it across various systems. With its rich set of features and capabilities, Mango Viewer serves as an invaluable resource for researchers and professionals within the medical imaging domain, facilitating innovative studies and advancements in the field.

3DimViewer is a compact, open-source tool specifically crafted for the effective visualization of medical DICOM images. By leveraging cutting-edge 3D graphics technology, it facilitates speedy and interactive visual representation of medical data tailored to various clinical and research requirements. The application boasts features like multiplanar reconstruction (MPR), volume rendering, and 3D surface rendering, which significantly broaden its applicability across different scenarios. Users are equipped with essential navigation functionalities such as zoom, pan, window/level modifications, and measurements of distance. Furthermore, 3DimViewer provides a simple and intuitive interface for examining DICOM metadata. It can retrieve DICOM image files from local storage or external devices and is available as a standalone executable for both Windows and macOS, which means no installation process is necessary. This accessibility makes 3DimViewer an appealing choice for students, researchers, and professionals in the medical field. The software’s ease of use and robust features position it as an indispensable asset in the domain of medical imaging. Overall, it effectively meets the diverse needs of its users, enhancing the experience of medical data visualization.

Miele-LXIV is a sophisticated 64-bit DICOM viewer and workstation developed by Alex Bettarini. The version designed for macOS is created using Objective-C and compiled with Xcode, and it is available for free download. On the other hand, the Windows and Linux editions have been completely re-engineered in C++ with the help of CMake and wxWidgets, currently featuring about 25% of the capabilities found in the macOS version. For users interested in the Windows version, it requires OpenGL (Core profile), and they can obtain a free evaluation version by contacting the developer directly. The Linux version, which is built with gcc, also necessitates OpenGL drivers (Core profile) and has been tested successfully on Ubuntu 24.04 and Linux Mint 22.1. Beyond serving as a DICOM workstation and viewer, Miele-LXIV also offers a range of additional functionalities. This initiative began in November 2014 as an offshoot of the popular open-source 32-bit project OsiriX, and it has since undergone extensive adaptations to become a fully functional 64-bit application, addressing many limitations of its predecessor. As Miele-LXIV evolves, the goal remains to enhance both user experience and operational capabilities even further, ensuring it meets the demands of its users.

RadiAnt DICOM Viewer serves as a powerful PACS DICOM viewer specifically designed for the medical imaging field, delivering fast and reliable performance alongside an intuitive interface. It enables users to retrieve studies from a variety of sources, including CDs, DVDs, local files, or PACS servers. The software is packed with vital features such as windowing, zooming, panning, rotating, and measurement capabilities. Additionally, with multi-touch functionality, users can effortlessly perform gestures for zooming, panning, and adjusting image windows. RadiAnt also supports multi-frame playback and cine loops, making it adept at handling ultrasound and cardiac studies efficiently. Users can compare multiple series or studies, synchronize scrolling for better analysis, and execute image fusion to enhance their evaluations. Furthermore, the application includes a sophisticated 3D reconstruction module that allows for multiplanar reconstructions, maximum intensity projections, and advanced volume rendering techniques. It also supports the export of images in various formats, including JPEG, DICOM, and video, while providing tools to anonymize sensitive data effectively. An important feature of RadiAnt is its ability to operate as a standalone executable, which adds to its portability and versatility across different environments. This viewer has become an essential asset for medical professionals aiming to streamline and improve their imaging workflows while ensuring high-quality analysis and accuracy. The comprehensive suite of tools offered by RadiAnt enhances the overall efficiency of medical imaging practices.

The DICOM Web Viewer, abbreviated as DWV, serves as a powerful, open-source platform designed for the visualization of DICOM images, crafted using JavaScript and HTML5, which functions flawlessly within modern web browsers without requiring additional plugins or installations. This tool allows users to interact with medical images in the DICOM format, utilizing popular web technologies and offering features such as window/level adjustments, zooming capabilities, panning, as well as measuring distances and angles, in addition to examining DICOM metadata. Furthermore, DWV is capable of managing different image layouts and handles both multi-frame and multi-series DICOM files effectively, ensuring a robust user experience. Users can easily annotate images using basic tools and load files directly from local storage or via URLs, greatly improving accessibility. The drag-and-drop functionality enhances file management, while the adaptable architecture permits developers to integrate the viewer into customized web solutions effortlessly. Continuously updated on GitHub, DWV emphasizes a responsive design to guarantee optimal usability across various devices, including desktops, tablets, and smartphones, making it a highly versatile tool for medical imaging professionals. In addition, the active community support and regular updates bolster the viewer's reliability and performance in managing medical image data efficiently. As such, DWV stands out as a crucial resource for healthcare providers in their imaging workflows.

MiNNOVAA is a company focused on advancing medical information technology, particularly in medical imaging software and the sharing of medical images. Emphasizing "medical imaging innovation," we distinguish ourselves through agility and cutting-edge technology in the development of our solutions. Our primary focus areas include creating medical image viewers, optimizing radiology workflows, and integrating artificial intelligence into diagnostic reporting. Our dynamic team consists of approximately 20 talented programmers and product managers, along with experts in marketing, sales, technical support, call center operations, and administration, all committed to initiating significant changes in medical imaging and improving healthcare experiences for individuals. We provide a holistic clinical imaging IT solution specifically designed for mid-sized hospitals and imaging clinics, offering a comprehensive suite of features such as core PACS software on-premise, a DICOM web viewer, multi-platform imaging workstation software, seamless integration with EHR/EMR/HIS systems, and a robust workflow engine/RIS. Our dedication to innovation and all-encompassing solutions ultimately seeks to transform the approach and application of medical imaging within healthcare environments. By continuously evolving our offerings, we aim to not only meet current needs but also anticipate future advancements in healthcare technology.