RDS (Rust DICOM Station) is an open-source DICOM workstation for radiotherapy research, analysis, and QA, written entirely in Rust. It loads complete radiotherapy studies (CT, MR and PET series, RTSTRUCT, RTDOSE, photon and ion RTPLAN, DICOM SEG, planar images, spatial and deformable registrations, and treatment records) into an integrated environment for visualization, comparison and quantitative analysis. Beyond the classic linked three-view layout and dual-dataset comparison, RDS provides image registration, structure propagation, DRR generation, dose-volume histograms, 4D motion analysis, interactive and AI-assisted segmentation, 3D visualization, and DICOM editing and export. The entire processing stack is native Rust: functionality normally provided through C/C++ or Python frameworks, including elastix- and plastimatch-style registration, ITK-style ray casting, TotalSegmentator, SegVol, and MedSAM2, is re-implemented directly in Rust without bindings to those frameworks.
The bundled 4D-Lung patient: two breathing phases as two rows of linked MPR views with their RTSTRUCT contours, and the 3D window showing the RTSTRUCT surfaces together with organs auto-segmented by the built-in TotalSegmentator engine.
- Viewing - parallel DICOM loading (compressed syntaxes included), true patient-space geometry, linked axial / sagittal / coronal views, W/L presets, dose colorwash and isodose lines, per-beam plan summaries, planar images (DX / CR / RTIMAGE), dark and light themes.
- Datasets - a patient ▶ study ▶ series tree per dataset; copy / move / remove / rename at every level with the reference chains kept intact; RT structure sets and segmentation series as tree nodes, contours and masks converting as they move between them; six-view comparison mode.
- Patient archive - a local PACS on plain folders and text sidecars: file a study, list patients without opening a DICOM file, load into either dataset, and send the structures and segmentations you drew back as derived objects under the original Study and Frame of Reference UIDs.
- Registration - rigid and B-spline after elastix (pyramids, stochastic sampling, ASGD), dense B-spline after plastimatch (analytic gradient, bending energy, L-BFGS, mean squares or Mattes mutual information) and plastimatch's landmark warp; any of them restricted to one structure or refined on top of a previous result. Every run reports its 6 DOF, displacement statistics, Jacobian determinant and folding; the vector field draws in the views and in 3D; fusion overlay; DICOM REG and Deformable Spatial Registration read and written; a known-transform simulator for QA.
- Structure propagation - contours and segmentations carried through a registration by per-voxel pull-back (no holes, any two grids), optionally refined on an enclosing structure first.
- 4D / motion - phases recognised into 4D groups; the reference phase registered to every other, targets propagated and their centroids tracked; peak-to-peak, drift, correlation with a reference structure, ITV generation, a results window with run-vs-run comparison and CSV export; structure comparison (Dice, HD95, surface distance) and transfer by relationship.
- DRR - plastimatch's exact Siddon tracer and ITK's interpolating ray-cast on one IEC cone-beam geometry, beam's-eye view from an RTPLAN beam, side by side with their difference.
- Dose-volume histograms - cumulative and differential DVHs of any
structures against any dose, sampled on the structure's own lattice;
D95%/D2cc/V20Gymetrics, protocol constraint checking, CSV export; verified against an analytic phantom. - Segmentation - spacing-aware 2D / 3D brush and eraser, geodesic region growing, undo, live 3D surfaces, mask ⇄ RTSTRUCT, DICOM SEG import and export (binary and fractional).
- Structure algebra - union / intersection / subtraction / symmetric difference with margins in patient directions (exact ellipsoids), crop, ring, cleanup.
- Body contour - the EXTERNAL structure without the couch, the chair or the mask, on CT and MR, classically or guided by TotalSegmentator's body network.
- Auto-segmentation - TotalSegmentator v2 rebuilt natively (117 structures): official nnU-Net weights converted without Python, a SIMD CPU engine or a wgpu GPU path (no CUDA), mean Dice 0.9995 against the reference.
- Prompt segmentation - SegVol rebuilt natively: box, click or free-text prompts ("liver", "tumor") for the structures no fixed-class model covers.
- Slice propagation - MedSAM2 (SAM 2.1 with its memory bank) rebuilt natively: box a structure on one slice, refine with include / exclude clicks, follow it through the stack at native resolution.
- Tools - DICOM export with an editable tag table, a model manager for every downloadable weight, a folder anonymizer with consistent UID regeneration, a synthetic RT-study generator; every tool window can be moved to its own monitor.
One language, one binary. All image processing runs on the CPU with rayon
and caching; the GPU (wgpu: DX12 / Vulkan / Metal) blits the UI and,
optionally, runs the networks. Long operations run on worker threads with
progress and cancellation. The module map, threading model, geometry
conventions and test suites are in
docs/architecture.md.
Requires a Rust toolchain (https://rustup.rs).
cargo build --release
cargo run --release -- example_data/lung_p1_4DCT_phase_000
cargo run --release -- example_data/lung_p1_4DCT_phase_000 example_data/lung_p1_4DCT_phase_050
cargo test --release
To try prompt segmentation on the bundled patient: put the crosshair on the
tumor, Tools ▶ 🧠 Prompt-segment dataset A…, prompt Box, ▶ Segment.
The engines fetch their weights on first use into one model folder
(%LOCALAPPDATA%\RustDICOMStation\models on Windows,
~/.local/share/RustDICOMStation/models on Linux), movable from any tool
window; each engine also has a headless CLI in examples/.
Windows, Linux and macOS are supported; --no-default-features builds a
CPU-only viewer without the GPU inference backend. Every push to main
publishes a release: a Windows installer
(rust-dicom-station-<version>-windows-x86_64.exe — shortcuts, "Open with"
on folders, the VC++ runtime check, optional weight prefetch, uninstaller)
and a Linux AppImage. The installer is its own crate in
installer/. No data at hand? File ▶ 🧪 Generate test
data… writes a complete synthetic RT study, and example_data/ ships a real
two-phase 4DCT (docs/example-data.md).
| docs/viewer.md | Loading, MPR views, dataset tree, comparison mode, interaction reference |
| docs/rt-objects.md | RTSTRUCT, RTDOSE, RTPLAN, REG, RTRECORD, reference chains |
| docs/registration.md | The four registration engines, local registration, analytics, vector fields, fusion, simulator, verification |
| docs/propagation.md | Carrying contours and segmentations across a registration |
| docs/motion-4d.md | 4D groups, the motion / ITV workflow, results, structure comparison and transfer |
| docs/drr.md | Digitally reconstructed radiographs: the two projectors and the geometry |
| docs/dvh.md | Dose-volume histograms: curves, metrics, constraint checking, export |
| docs/segmentation.md | Brush / eraser / region growing, 3D view, mask → RTSTRUCT |
| docs/structure-algebra.md | Boolean operations, margins, cropping, cleanup |
| docs/body-contour.md | The body / EXTERNAL contour on CT and MR, verification |
| docs/auto-segmentation.md | The pure-Rust TotalSegmentator: models, pipeline, engines, validation, classes, licensing |
| docs/segvol.md | Prompt-driven segmentation: the SegVol re-implementation |
| docs/medsam2.md | Propagating a prompt through a stack: the MedSAM2 re-implementation |
| docs/pacs.md | The local patient archive: window, on-disk layout, filing, loading, sending changes back |
| docs/export-and-tools.md | DICOM export, the model manager, anonymizer, test-data generator |
| docs/architecture.md | Design, functional overview, module map, threading, the model folder, conventions, testing |
| docs/release-versioning.md | How versions and releases are produced |
| docs/example-data.md | Bundled patient data, source and citations |
| installer/README.md | The Windows installer: building it, what it installs, silent switches |
The code is MIT-licensed. The bundled example data is TCIA 4D-Lung patient P102, redistributed under CC BY 3.0 (cite it as described in docs/example-data.md). Auto-segmentation uses TotalSegmentator's Apache-2.0 "total"-task weights (cite Wasserthal et al. (Radiology AI 2023) and nnU-Net (Isensee et al., Nature Methods 2021) as described in docs/auto-segmentation.md). Prompt segmentation re-implements SegVol (Du et al., NeurIPS 2024) and slice propagation MedSAM2 (Ma et al., 2025); their weights are only ever downloaded from Hugging Face to your own machine at your request and are never redistributed; see docs/segvol.md and docs/medsam2.md.
This software is a viewer for research and QA convenience. Not a medical device, and not for clinical decision-making.