In the era of AI, everyone can build software tailored to their own needs. OpenDicomViewer is a free, native macOS DICOM viewer — designed to be forked, customized, and made your own.
Requires macOS 14.0+ (Sonoma) · Apple Silicon
Why OpenDicomViewer
Native performance, clinical tools, and an architecture designed for customization.
Built with SwiftUI and Metal. No Electron, no web views — just native macOS speed with GPU-accelerated rendering.
Ruler, angle, and ROI measurements with real-time preview lines. Window/level controls with histogram display.
Side-by-side, stacked, and quad views with synchronized scrolling, zoom, and cross-reference lines.
One-click multiplanar reconstruction. GPU-powered MIP, MinIP, and average projections with adjustable slab thickness.
MIT licensed. Fork it, customize it, use it however you want. No restrictions, no strings attached.
Clean, readable code with minimal abstraction. Designed to be extended with AI coding assistants like Claude or Copilot.
Demo
Features
Professional DICOM viewing capabilities in a lightweight, focused application.
A mini histogram displays the pixel value distribution at a glance. The current window width and level are overlaid directly on the histogram so you can instantly understand the contrast mapping.
Hover or drag the right-side scrollbar to see a thumbnail preview of any slice. Navigate hundreds of images without losing your place.
Browse every DICOM metadata tag for the active image. Switches automatically when you change panels. Cursor readout shows HU values and patient coordinates in real-time.
Side-by-side, stacked, and quad layouts with drag-and-drop series assignment. A miniature panel grid icon next to each series in the sidebar shows exactly which pane displays which series.
Instantly reconstruct sagittal and coronal views from any axial series. GPU-accelerated MIP, MinIP, and average projections with adjustable slab thickness for fine control.
Ruler, angle, and ROI statistics with dashed preview lines that follow your cursor between clicks. Millimeter-accurate when pixel spacing metadata is available.
Link all panels to scroll, zoom, and pan in sync. Spatial z-location matching ensures panels showing different series display the same anatomical position.
See where other panels' slice planes intersect the current view for spatial orientation across series.
Custom pure-Swift DICOM parser with incremental scanning. The first image appears before the rest of the study finishes loading in the background.
Handles all common compressed transfer syntaxes via DCMTK and OpenJPEG integration, including JPEG, JPEG-LS, and JPEG 2000.
Keyboard-First
Extensive keyboard shortcuts for every tool and action. Keep your hands on the keyboard.
Get Started
Grab the latest release, open the DMG, and drag OpenDicomViewer to your Applications folder. The app is signed and notarized — no Gatekeeper warnings.
Download DMGClone the repo and run the build script. Pre-built native libraries are included — no extra setup needed.
# Clone and build
git clone https://github.com/jnheo-md/open-dicom-viewer.git
cd OpenDicomViewer
./scripts/package_app.sh
# Install (optional)
cp -r OpenDicomViewer.app /Applications/About the Author
Fork it, modify it with an AI assistant, and make it yours.
Assistant Professor, Department of Neurology · Yonsei University College of Medicine
Stroke neurologist and neurointerventionist with 25 years of passion for software engineering. Named MIT Technology Review Innovators Under 35 (Korea, 2021) for applying AI and machine learning to stroke medicine. OpenDicomViewer was born from the conviction that in the era of AI, everyone should be able to customize open-source tools to meet their own needs.