AIHealth
On-premise clinical platform with local LLMs, RAG on FHIR/DICOM data, diagnostic support, remote follow-up. Architecture designed for the MDR pathway.
Discover AIHealth →
Digital Health
Medical software development compliant with CE and MDR regulatory standards. Clinical decision support systems, AI integration in clinical workflows.
Discover →From academic research to a clinical platform
While ITK provides algorithms for image analysis and VTK handles visualisation, the medical image computing community needed a application platform — end-user software with graphical interface, clinical case management, integration among segmentation, registration, visualisation and measurement modules — usable by radiologists, neurosurgeons and researchers without programming skills.
3D Slicer answered this need, born in the late 1990s as a collaboration between the Surgical Planning Laboratory of the Brigham and Women’s Hospital (Boston) and the MIT AI Lab, with founders including Ron Kikinis (BWH, Harvard Medical School), Steven Pieper (Isomics Inc.), Bill Lorensen (GE Research), David Gering (MIT) and Martin Halle (BWH).
The first public release of the software dates to 1998-1999. Version 2.0 (2000) introduced the modular architecture that characterises the system today. After four years of developments, the software is at version 2.6 (released during 2004), stable and in clinical use at several US and European centres.
NA-MIC: an NIH consortium
In 2004 the US National Institutes of Health, through the NIH Roadmap for Biomedical Research programme, awarded a grant to the NA-MIC consortium — National Alliance for Medical Image Computing — coordinated by Ron Kikinis (BWH) and Ross Whitaker (University of Utah). The consortium brings together the leading US competences in medical image computing:
- BWH / Harvard Medical School — Surgical Planning Laboratory
- MIT CSAIL — Artificial Intelligence Laboratory
- University of Utah — Scientific Computing and Imaging Institute
- UNC Chapel Hill — Neuro Image Research and Analysis Laboratory
- Isomics, GE Research, Kitware — industrial partners
NA-MIC’s mission is to build an open source software infrastructure for biomedical image computing, with 3D Slicer as main application platform and ITK/VTK as base libraries. The model is that of the National Centers for Biomedical Computing — distributed research centres producing reusable software for the whole NIH-funded scientific community.
3D Slicer’s architecture
3D Slicer is written mainly in C++ with a Tcl/Tk interface (as of 2004). The core uses ITK for analysis and VTK for visualisation; the interface is built with KWWidgets, a Tk-based Kitware toolkit. The system is cross-platform (Linux, Windows, Mac OS X), distributed under the BSD licence.
Architectural components:
- MRML (Medical Reality Markup Language) — central data model that represents clinical cases as scenes: image volumes, segmented 3D models, transforms, annotations. XML persistence format
- Modules — loadable software components that add specific functionality (brain segmentation, deformable registration, DTI fibre tracking, ROI analysis). Each module is independent but shares the MRML data model
- Render views — axial/sagittal/coronal 2D views synchronised with 3D views of surface models, with shared cursor
- Command Line Interface (CLI) Modules — pattern in which complex modules are external executables invoked with standard parameters, allowing integration of tools written in any language as long as they respect the XML parameter description contract
Main clinical modules
As of 2004 3D Slicer includes modules of immediate clinical relevance:
- Segmentation editor — interactive drawing tools, thresholding, region growing, smoothing, island removal
- Fibre tracking — deterministic DTI (Diffusion Tensor Imaging) tractography to visualise cerebral white matter fibre bundles
- Registration — rigid, affine, deformable between volumes (e.g. pre-operative and intra-operative)
- Volumetric analysis — volume calculation of segmented structures
- Fiducials — 3D anatomical reference points for landmark-based registration and planning
- Measurements — distances, angles, intensity measurements
- DICOM navigator — DICOM import/export, with parsing of vendor-specific private tags
Clinical use cases
3D Slicer is in use in several clinical scenarios, primarily translational research:
- Neurosurgery planning — 3D reconstruction of the patient case from pre-operative MRI, identification of the tumour and critical structures (fibre bundles, eloquent cortex), planning of the surgical approach. Some centres also use intra-operative image-guided surgery with intra-operative MRI and deformable registration to the pre-operative data
- Neuroimaging research — structural morphometry studies, DTI, fMRI, with reproducible pipelines
- Cardiovascular — cardiac structure quantification from CT/MRI
- Oncology — lesion delineation for radiotherapy planning, treatment response assessment
- Orthopaedics — hip and knee prosthesis planning from CT
The Surgical Planning Laboratory at BWH — hosting the project’s reference centre — has accumulated over ten years of clinical experience with the software, with publications and validated cases.
The open source approach
The development model combines academic and industrial contribution:
- Public repository with version control (CVS in 2004, later Subversion, Git in the future)
- Active technical mailing list with core developers and users
- Project Weeks — periodic co-development events where consortium members and users physically work together for days on the platform, discuss architecture, integrate contributions
- Code review for every significant change
- Continuous integration on cross-platform build servers (Kitware’s CTest/CDash)
The BSD licence allows use also in commercial products. Several surgical system manufacturers (BrainLAB, Medtronic) incorporate portions of 3D Slicer or use its formats as reference.
Relationship with other tools
3D Slicer is not the only open source medical imaging framework:
- MedINRIA (INRIA, France) — kindred platform, specialised on neuroimaging and diffusion tensor imaging
- MIPAV (Medical Image Processing, Analysis and Visualization) — NIH Bethesda, Java-based
- OsiriX — DICOM viewer for Mac OS X, oriented to daily clinical practice (originally BSD-licensed, later changing)
- Amira (commercial) — widespread in biomedical research
3D Slicer stands out for:
- Algorithmic depth of the underlying ITK/VTK ecosystem
- Modular and extensible architecture
- Support for advanced research pipelines (DTI, fMRI, deformable registration)
- Close relationship with the academic medical image computing community
Outlook
With the 2004 NA-MIC grant and 3D Slicer’s role as the consortium’s application platform, the project enters a phase of expansion. BWH’s published roadmaps foresee:
- GUI rewrite with more modern toolkits (presumably Qt in future versions)
- Slicer 3.0 as the next major release, with extended architecture
- Integration with clinical registry systems for translational studies
- Modules for longitudinal analyses — comparing exams of the same patient over time
- Interoperability standardisation with DICOM and HL7
For Italian clinical research groups and neurosurgery centres that today adopt commercial solutions, 3D Slicer represents an alternative without licensing costs, with the possibility of contributing technically to the platform and integrating it into their clinical flows. The learning curve is non-trivial — requires specific training — but the support community is active and the clinical applications are widely documented in the literature.
References: 3D Slicer (www.slicer.org). Surgical Planning Laboratory, Brigham and Women’s Hospital. MIT Computer Science and AI Laboratory. National Alliance for Medical Image Computing (NA-MIC), NIH Roadmap 2004 grant. ITK, VTK, KWWidgets (Kitware). BSD licence.