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3D Slicer & NA-MIC: Overview and Applications

3D Slicer & NA-MIC: Overview and Applications. Steve Pieper, PhD. Acknowledgments.

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3D Slicer & NA-MIC: Overview and Applications

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  1. 3D Slicer & NA-MIC:Overview and Applications Steve Pieper, PhD

  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, N. Aucoin, K. Hayes, S. Barre, W. Plesniak, R. Gollub, S. Pujol and many more….

  3. Overall Goal for NA-MIC • Why Medical Research? • To Help Patients!

  4. How to Make this Happen? • Enable World-Class Biomedical Research • Develop a Comprehensive Platform • Create a Community of Developers and Users • Ensure Maximum Reusability of Software

  5. Autism Development • Correlate Localized Brain Development with Observed Behavioral Characteristics of Autism • Structural and Diffusion Imaging at 2yo and 4yo • Cortical Thickness and Subcortical Volume Metrics Blue: Growth Red: Atrophy Green: No Change Images: Hazlett et al

  6. Schizophrenia • Structural and Diffusion to Discover Disruptions Correlated with Symptoms • First Generation DBP • Regional Analysis of FA Based on Manual Tract Identification • Second Generation DBP • Stochastic Tractography, Improved Metrics, Registration Images Ngo et al.

  7. Prostate Disorders • Segmentation tool for Brachytherapy Planning and Biopsy • Navigation for Biopsy • Future FUS and Robot Applications Haker SJ, Mulkern RV, Roebuck JR, Barnes AS, Dimaio S, Hata N, Tempany CM.: Magnetic resonance-guided prostate interventions. Top Magn Reson Imaging. 2005 Oct;16(5):355-68.

  8. Lupus Lesions • Automatic Analysis of White Matter Abnormalities in Neuropsychiatric SLE (Lupus) • About 1.5 Million Americans with Lupus, Underlying Pathologic Processes Unknown – Possibly Vascular Hypointense on T1 Hyperintense T2 Hyperintense on FLAIR Images: Bockholt et al

  9. Patient-Specific Finite Element Model Development • Iowa: Kiran H. Shivanna, Vincent A. Magnotta, Nicole M. Grosland, • NA-MIC: Steve Pieper, Curt Lisle • Automate the generation of high quality hexahedral meshes • Inclusion of soft tissues such as cartilage • Automated Segmentation • Validation • Published / Accepted • Devries NA, Gassman EE, Kallemeyn NA, Shivanna KH, Magnotta VA, Grosland NM. Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning. Skeletal Radiol. 2008 Jan;37(1):35-42. Epub 2007 Oct 25. • Gassman EE, Powell SM, Kallemeyn NA, DeVries NA, Shivanna KH, Magnotta VA, Ramme AJ, Adams BD, Grosland NM, Automated Bony Region Identification Using Artificial Neural Networks: Reliability and Validation Measurements. Skeletal Radiology (accepted / online). • Grant funding NIH • R21 (EB001501) • R01 (EB005973)

  10. Chlorocebus aethiops (vervet) Alcohol and Stress • Primate (Rhesus and Vervet) Models to Study the Effect of Chronic Alcohol Self-Administration on Brain Structure and Function • Compare Mother-Reared vs. Nursery-Reared • Apply Automated Segmentation Tools to Assess Cortical and Subcortical Regions (EMSegmenter, Pohl et al) * Rhesus template and atlas graciously provided by Martin Styner and collaborators Images: Wyatt et al

  11. Image Guided Therapy (IGT) • Is the active visualization of medical images to aid in decision making during a procedure. • Allows physician to • See Beyond the Surface • DefineTargets • Control the Interventions • Enables new procedures, decreases invasiveness, optimizes resection Dimaio SP, Archip N, Hata N, Talos IF, Warfield SK, Majumdar A, Mcdannold N, Hynynen K, Morrison PR, Wells WM 3rd, Kacher DF, Ellis RE, Golby AJ, Black PM, Jolesz FA, Kikinis R.: Image-guided neurosurgery at Brigham and Women's Hospital.IEEE Eng Med Biol Mag. 2006 Sep-Oct;25(5):67-73

  12. Mapping Provided by Archip, Warfield Alignment of all pre-operative datasets to the intra-operative images achieved during the neurosurgery. Archip N, Clatz O, Whalen S, Kacher D, Fedorov A, Kot A, Chrisochoides N, Jolesz F, Golby A, Black PM, Warfield SK. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage. 2007 Apr 1;35(2):609-24

  13. Liver Lesion Treatment • Needle Placement for CT-Guided Radio Frequency Ablation (RFA) • Unresectable Hepatocellular Carcinoma (HCC) and Liver Metastases • Open Source Environment • Slicer3 and IGSTK • Automated Liver Segmentation • Path Planning Tools for Multiple Overlapping Lesions • Validation on Swine Model Images: Cleary et al

  14. NA-MIC Governance Software Sharing: http://grants1.nih.gov/grants/guide/rfa-files/RFA-RM-04-003.html • …software should be freely available … • …permit the commercialization of enhanced or customized versions … • …include the ability of researchers outside the center and its collaborating projects to modify the source code and to share modifications …

  15. BSD Style License • Open Source • No license fees • No restriction on use • Clinical and commercial uses do not require our permission • No guarantees • User is responsible for making sure that the software works, we promise nothing. Same for compliance with all regulations. • E.g. if you want to use our software for clinical trials, you have to apply for the proper authorizations at your institution • NO requirement to give your code back to open source (NOT viral). • You can contribute code back to us, if you want to do that and it is our decision if we will accept it. • Acknowledge our contribution • See http://www.slicer.org for more information

  16. FOSS – A Public Highway… • Open-source is like a Public Road System • Provides Infrastructure for a Variety of Uses • Driveways can Lead to Anything: • a Public Park • a Private Facility FOSS= Free Open Source Software Provided by Pieper, Kikinis

  17. Leadership: BWH: Ron Kikinis, (Overall PI) Core 1 Algorithms Utah: Ross Whitaker (Core 1 PI) MIT: Eric Grimson UNC: Guido Gerig MGH: Bruce Fischl, Dave Kennedy GaTech: Allen Tannenbaum Core 2 Engineering Kitware: Will Schroeder (Core 2 PI) GE: Jim Miller Isomics: Steve Pieper UCSD: Mark Ellisman UCLA: Art Toga Core 3 DBP 2004-2007 BWH: Martha Shenton Dartmouth: Andy Saykin UCI: Steve Potkin UofT: Jim Kennedy DBP 2007 UNC: H. Cody BWH: M. Kubicki Mind Institute: J. Bockolt Queens University: G. Fichtinger Core 4 Service Kitware: Will Schroeder Core 5 Training MGH: Randy Gollub Core 6 Dissemination Isomics: Steve Pieper, Tina Kapur Core 7 Management BWH: S. Manandhar NA-MIC: A Network of Peers Provided by Pieper, Kikinis

  18. Dissemination and Training • National and International Events • MIT, MGH, UNC, EPFL, NIH, UNM, UCSD… • All Materials on Wiki • Project Weeks • Full Week Each Summer • ½ Week at Winter AHM • Workshops • MICCAI 2005, 2006, 2007, 2008.. • OHBM, RSNA, Munich, NCI…

  19. What is 3D Slicer? • Reference NA-MIC Kit Implementation • A platform for image analysis and visualization • Current Releases 2.7 and 3.0 • 2.7 most features and documentation • 3.0 focus of current activity • A freely-downloadable program • Source code and executables available for Windows, Linux, and Mac OS X • Slicer is a research platform: • NOT an FDA approved medical device • NOT finished – some parts will work better than others

  20. Slicer Features • I/O: • Image: DICOM, NIfTI, Analyze, Meta, NRRD, MGZ... • Surface: vtk, vtp, stl, freesurfer, fiber bundle • Coordinate Systems: Patient-Referenced Data • Visualization: Volume Rendering, Surfaces, Slices Planes, Clipping, Volume Overlays... • Filtering: Denoising, Nonlinear/Aniostropic Smoothing, Format Conversion • Registration: Multimodal (e.g. CT/MR), Rigid, Affine, BSpline. Apply Transforms to other volumes.

  21. More Slicer Features • Segmentation: Manual Editor, Semi-Automated (Region Growing), Statistical Classifiers, Atlas Based • Diffusion Imaging: DICOM Import, Tensor Tools, Tractography • Quantification: Volume Measurements, Points, Lines • Real-time: Networked Trackers and Volume I/O • And more... • Meshing, Fiducials, Batch Processing, Remote Data I/O,

  22. Integrated Scene • XML-Based MRML File Stores Scene Description • Volumes (Images, Label Maps) • Models • Hierarchical Affine Transforms • Scene Data (Cameras, Colors, Fiducials, etc). • Manipulated in World Coordinates based on Patient RAS (Right-Anterior-Superior) Provided by N. Archip et al

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