A fast, modern DICOM image viewer built with Go and the Fyne toolkit.
- Multi-format DICOM support - Load single files, directories, or multi-frame DICOM
- 3D Volume Rendering - Real-time volume visualization with adjustable opacity and thresholds
- 2D Slice Navigation - Browse through axial slices with window/level controls
- Medical Imaging Presets - Built-in window presets for Soft Tissue, Bone, Lung, Brain, and Liver
- Material Segmentation - Color-coded tissue classification (Background, Soft Tissue, Dense Tissue, Bone, Metal)
- JPEG-LS Compression - Native support for lossless DICOM compression
- Cross-platform - Runs on macOS, Linux, and Windows
go install github.com/jpfielding/goxel/cmd@latestOr build from source:
git clone https://github.com/jpfielding/goxel.git
cd goxel
go build -o goxel ./cmd# Open a DICOM file
goxel goxel -p /path/to/file.dcm
# Open a directory of DICOM slices
goxel goxel -p /path/to/dicom/directoryCombine multiple DICOM slice files into a single multi-frame DICOM with optional compression:
# Merge with JPEG-LS compression (default)
goxel merge -i /path/to/slices -o output.dcm
# Merge without compression
goxel merge -i /path/to/slices -o output.dcm -c=falsegoxel decode -u /path/to/file.dcm| Control | Action |
|---|---|
| Slice Slider | Navigate through image slices |
| Window Level | Adjust brightness/contrast center |
| Window Width | Adjust brightness/contrast range |
| Z Scale | Adjust 3D volume aspect ratio |
| Material Sliders | Adjust tissue threshold boundaries |
| Opacity Slider | Control 3D rendering transparency |
pkg/
├── dicom/ # DICOM parser and writer
│ ├── module/ # DICOM IOD modules (Patient, Study, Series, etc.)
│ ├── tag/ # DICOM tag definitions
│ └── transfer/ # Transfer syntax handling
├── compress/ # Image compression codecs
│ ├── jpegls/ # JPEG-LS lossless
│ ├── jpegli/ # JPEG lossy
│ ├── jpeg2k/ # JPEG 2000
│ └── rle/ # Run-length encoding
├── volume/ # 3D volume rendering
└── goxel/ # Fyne UI application
Inspired by the Fyne DICOM Viewer. Aided heavily by Claude.ai, esp in the opengl work.
MIT
