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3D Slicer

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F. Jolesz, R. Kikinis, C. Tempany, P. Black, S. Wells, CF. ... Haker SJ, Mulkern RV, Roebuck JR, Barnes AS, Dimaio S, Hata N, Tempany CM. ... – PowerPoint PPT presentation

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Title: 3D Slicer


1
3D Slicer NA-MICOverview 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 Oct16(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
    Jan37(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
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-Oct25(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 135(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
NA-MIC A Network of Peers
  • 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
  • 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

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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