NA-MIC National Alliance for Medical Image Computing 3D Slicer and the NA-MIC Kit for IGT Research Steve Pieper, PhD NAC, SPL, NA-MIC, BIRN, NCIGT, Isomics, Inc. Founder and CEO of Isomics, Inc. a technology development company that works closely with multiple research institutions on projects including NIH grants and software development. Much of this work is done in collaboration with the Surgical Planning Laboratory at BWH.

National Alliance for Medical Image Computing 2 Acknowledgments F. Jolesz, R. Kikinis, C. Tempany, P. Black, S. Wells, CF. Westin, M. Halle, N. Hata, T. Kapur, A.Tannenbaum, M. Shenton, E. Grimson, P.Golland, W.Schroeder, J. Miller, W. Lorensen, A. Yarmarkovich, N. Aucoin, K. Hayes, S. Barre, W. Plesniak, D. Marcus, and many more….

National Alliance for Medical Image Computing 3 Goals NA-MIC Kit: Software and Methodologies for Medical Image Computing –Facilitate Research –Promote Interoperability Stable, Cross-Platform Run Time Environment –Full set of core features Flexible Module Architecture –Plug-ins added as needed

National Alliance for Medical Image Computing 4 Fully Open, Interoperable Components End User Application –3D Slicer Image Analysis, Visualization, and GUI libraries –ITK, VTK, KWWidgets Large Scale Data Processing Tools –Batchmake, XNAT, BIRN GRID tools Software Engineering Tools –CMake, Dart, CTest, CPack Provided by Pieper, Kikinis

National Alliance for Medical Image Computing 5 Where Does Slicer Fit? Shared Platform for Research and Applications Ensure Data Compatibility Enable Algorithms at Run Time As Needed Common Developer Vocabulary Consistent User-Centered Interface Leverage NIH Investment Best of Breed Open Source Tools Collaborator Expertise Unique Environment National Scope Clinical and Research Commercial and Academic Image provided by A. Golby, F. Talos, P. Black Slicer is a research platform: –NOT an FDA approved medical device –NOT finished – some parts will work better than others

National Alliance for Medical Image Computing 6 Image/Scene Management XML-Based MRML File Stores Scene Description –Volumes (Images, Label Maps) –Models –Hierarchical Affine Transforms –Scene Data (Cameras, Colors, Fiducials, etc) –Undo/Redo, Scene Snapshots Careful Attention to Coordinate Systems –Scalar Images –Diffusion Images –Time Series (fMRI) –Visualization Provided by S. Pieper

National Alliance for Medical Image Computing 7 More Slicer3 Features in Development Fully Scriptable in Tcl or Python –Links to scipy, numpy, pylab, matplotlib SlicerDaemon –All Data and API available by connecting to socket Execution Model –Very easy to develop plug-in modules that run either as shared libraries or command line executables Experiment Control –Ties to databases and distributed computing to run analyses on large populations –Informatics Interfaces XCEDE, XNAT, BatchMake Much more on the drawing board… –3D Widgets, DICOM WG23, caBIG…

National Alliance for Medical Image Computing Modularity Project Keep the base package “lean and mean” Modules have individual identity –Per-module web site, svn, downloads, mailing lists, wiki… Allow users to assemble their own set of tools –Customized ‘Bundles’ by task or application Easy to download compatible extensions –Analogous to Firefox extensions –Integrate extension builds into developer/nightly/release processs NITRC Supplement to NA-MIC helping to pay for needed infrastructure (Neuroimaging Informatics Tools and Resources Clearinghouse) –NITRC can host neuroimaging projects (gforge implementation) 8

National Alliance for Medical Image Computing 9 Base Features vs. Modules FeaturesBaseModules VisualizationMRML: Models, Volumes, Volume Rendering, Fiducials, Continuum Meshes, Labeled Data Can create custom MRML Nodes and behavior FilteringNoneCommand Line Modules RegistrationTransform Display and Edit, Save/RestoreCalculate Transforms, Resample Data SegmentationLabel Maps, Parcellated SurfacesSegmentation Algorithms QuantificationLabel, Image, Volume Statistics; Numpy access to MRML Applications in Python or MATLAB Real-time IntegrationVTK Rendering, KWWidgets framework, Tracker Support (as Transforms) Direct Manipulation of the MRML Scene; 2D/3D Widgets; Device Interfaces Diffusion ImagingDWI, DTI, Fiber BundlesTractography, Clustering, Atlases Applications“Bundles” of Modules in Distribution: Registration, Editor, some Filters, Customized Extensions, Domain- specific code, Optimized Interfaces…

National Alliance for Medical Image Computing 10 It’s all great, but… A few caveats: It’s a big, distributed group –Pro: “Wisdom of the Crowds” –Con: “Designed by Committee” It’s all research –Constantly evolving –Never enough documentation –Plurality of approaches How well we work together will determine the impact of our work