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NA-MIC National Alliance for Medical Image Computing 3D Slicer & NA-MIC: Overview and Applications Steve Pieper, PhD.

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Presentation on theme: "NA-MIC National Alliance for Medical Image Computing 3D Slicer & NA-MIC: Overview and Applications Steve Pieper, PhD."— Presentation transcript:

1 NA-MIC National Alliance for Medical Image Computing http://na-mic.org 3D Slicer & NA-MIC: Overview and Applications Steve Pieper, PhD

2 National Alliance for Medical Image Computing http://na-mic.org 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 National Alliance for Medical Image Computing http://na-mic.org 3 Overall Goal for NA-MIC Why Medical Research? –To Help Patients!

4 National Alliance for Medical Image Computing http://na-mic.org 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 National Alliance for Medical Image Computing http://na-mic.org Outline Survey of Application Targets Introduction to NA-MIC Overview of 3D Slicer Features 5

6 National Alliance for Medical Image Computing http://na-mic.org 6 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

7 National Alliance for Medical Image Computing http://na-mic.org 7 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.

8 National Alliance for Medical Image Computing http://na-mic.org 8 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.

9 National Alliance for Medical Image Computing http://na-mic.org 9 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 T1Hyperintense T2Hyperintense on FLAIR Images: Bockholt et al

10 National Alliance for Medical Image Computing http://na-mic.org 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)

11 National Alliance for Medical Image Computing http://na-mic.org 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) 11 Chlorocebus aethiops (vervet) * Rhesus template and atlas graciously provided by Martin Styner and collaborators Images: Wyatt et al

12 National Alliance for Medical Image Computing http://na-mic.org 12 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 Image Guided Therapy (IGT) 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

13 National Alliance for Medical Image Computing http://na-mic.org 13 Alignment of all pre-operative datasets to the intra-operative images achieved during the neurosurgery. Provided by Archip, Warfield Mapping 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

14 National Alliance for Medical Image Computing http://na-mic.org 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 14 Images: Cleary et al

15 National Alliance for Medical Image Computing http://na-mic.org 15 NA-MIC: A Network of Peers 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 Provided by Pieper, Kikinis

16 National Alliance for Medical Image Computing http://na-mic.org 16 NA-MIC Governance NIH Goals for 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 …

17 National Alliance for Medical Image Computing http://na-mic.org 17 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

18 National Alliance for Medical Image Computing http://na-mic.org 18 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

19 National Alliance for Medical Image Computing http://na-mic.org 19 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…

20 National Alliance for Medical Image Computing http://na-mic.org 20 Project Week Next Week (June 23-27) at MIT Stata Center > 100 Participants 32 Institutions 6 Countries 5 Companies Project Teams Sit and Work Together Face to Face Communication

21 National Alliance for Medical Image Computing http://na-mic.org 21 What is 3D Slicer? Reference NA-MIC Kit Implementation A platform for image analysis and visualization Current Releases 2.7 and 3.2 –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 –All Code Reusable Slicer is a research platform: –NOT an FDA approved medical device –NOT finished – some parts will work better than others

22 National Alliance for Medical Image Computing http://na-mic.org 22 Slicer Features I/O: –Image: DICOM, NIfTI, Analyze, Meta, NRRD, MGZ... –Surface: vtk, vtp, stl, freesurfer, fiber bundle Coordinate Systems: All Data is Patient-Referenced 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.

23 National Alliance for Medical Image Computing http://na-mic.org 23 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, Extensible in C++/Tcl/Python, Slicer Daemon...

24 National Alliance for Medical Image Computing http://na-mic.org 24 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

25 National Alliance for Medical Image Computing http://na-mic.org Integrated Visualization 25

26 National Alliance for Medical Image Computing http://na-mic.org Volume Rendering 26

27 National Alliance for Medical Image Computing http://na-mic.org 3D Widgets 27

28 National Alliance for Medical Image Computing http://na-mic.org Light Box Viewing 28

29 National Alliance for Medical Image Computing http://na-mic.org Scene Snapshot 29

30 National Alliance for Medical Image Computing http://na-mic.org Label Map Editor 30

31 National Alliance for Medical Image Computing http://na-mic.org Rich I/O Support 31

32 National Alliance for Medical Image Computing http://na-mic.org Diffusion Volumes 32

33 National Alliance for Medical Image Computing http://na-mic.org Remote Data I/O 33

34 National Alliance for Medical Image Computing http://na-mic.org OpenIGTLink 34

35 National Alliance for Medical Image Computing http://na-mic.org Registration 35

36 National Alliance for Medical Image Computing http://na-mic.org Segmentation 36


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