NA-MIC National Alliance for Medical Image Computing National Alliance for Medical Image Computing: NAMIC Ron Kikinis, M.D.

National Alliance for Medical Image Computing Overview Introduction Core 1 Core 2 Core 3 Support Cores Slicer Demo

National Alliance for Medical Image Computing Introduction What is our problem? What is our science?

National Alliance for Medical Image Computing What is our problem? Imaging: Data Acquisition –Increasing production –Increasing complexity Image Computing: –Information extraction –Example: Diffusion Tensor Imaging

National Alliance for Medical Image Computing Provided by Meier, Mamata, et al. Line scan diffusion tensor imaging Diffusion weighting through sensitivity for slow motion 6 volume acquisitions provide the components of the diffusion tensor 20 min to 1 hour depending on scanner and resolution Imaging

National Alliance for Medical Image Computing Diffusion Tensor MRI Stejskal-Tanner formula: Provided by Westin, et al.

National Alliance for Medical Image Computing Image Computing Too much data Need to identify relevant information

National Alliance for Medical Image Computing All Tensors Provided by Odonnell, et al.

National Alliance for Medical Image Computing Visualization and Interaction Provided by Westin, et al.

National Alliance for Medical Image Computing From Tensors to Tracts Provided by Westin, et al.

National Alliance for Medical Image Computing DTI Visualization Provided by O’Donnell, Westin et al. Thickness and color describe the quality of fit

National Alliance for Medical Image Computing DT-MRI Tractography Provided by Westin et al.

National Alliance for Medical Image Computing Fusion of DTI and fMRI F. Talos, Westin, Wells et al.

National Alliance for Medical Image Computing What is our science? Computational tools for image analysis Software engineering methods and applications for image analysis

National Alliance for Medical Image Computing Provided by S. Timoner Capturing Variability

National Alliance for Medical Image Computing Shape Description Map of shape variability of the Thalamus Blue: high variability 4 years of graduate student work Provided by S. Timoner

National Alliance for Medical Image Computing Structure

National Alliance for Medical Image Computing Overview Introduction Core 1 Core 2 Core 3 Support Cores Slicer Demo

National Alliance for Medical Image Computing Core 1: Overview Harvard Georgia TechUNC UtahMIT Segmentation Registration Foundational Methods Structural Features and Statistics Connective Features and Statistics 1. Shape and Atlas Based Segmentation 2. Statistical Shape Analysis 3, DTI Connectivity Analysis 1. Diffusion-based Registration 2.Group Effect Maps 3. Automatic Segmentation 1. DTI Processing 2. Surface Processing 3. PDE Implementations 1. Combined Statistical/PDE Methods 1. Quantitative DTI Analysis 2. Cross-Sectional Shape Analysis 2. Stochastic Flow Models

National Alliance for Medical Image Computing Core 1: Objectives Computational tools for image analysis –Extract anatomical structures at many scales –Measure properties of extracted structures –Determine connectivity between extracted structures –Relate disease factors to measurements

National Alliance for Medical Image Computing UNC – Gerig: DTI Fiber statistics Structural analysis of DTI tracts –Extraction and analysis –Measurements along tracts –NAMIC-ready in ITK Uncinate fasciculus Major fiber tracts

National Alliance for Medical Image Computing Overview Introduction Core 1 Core 2 Core 3 Support Cores Slicer Demo

National Alliance for Medical Image Computing Core 2: Overview GE IsomicsUCSD UCLAKitware Software Integration Software Engineering Software Quality Software Engineering Tools Data Access Tools 1. Cross-platform Build 2. Cross-platform Distribution 3. Cross-language API’s1. Software Architecture2. Software Process3. Software Quality1. Graphical programming interfaces 2. Coordinate pre-compiled tools 3. Data format interpreters1. DBP Applications 1. Grid Middleware 2. Data Grid 2. Application Methodology Distributed Computing Applications 3. Data Mediation3. Application Quality Assurance

National Alliance for Medical Image Computing Core 2: Objectives Create a software development environment and culture that encourages and supports scientific algorithm innovation while at the same time produces high quality software that meets the needs of the driving biological projects

National Alliance for Medical Image Computing The Open Source Model Open source software is an important enabling technology for translational research in medical image computing

National Alliance for Medical Image Computing NA-MIC Kit Application –3D Slicer Toolkits –ITK, VTK, LONI pipeline Software Engineering Tools –Cmake, Ctest, Dart2, Doxygen, CableSwig, others

National Alliance for Medical Image Computing Isomics - Pieper End User Application Engineering –Based on 3D Slicer ( –Cross-platform GUI for Segmentation, Registration, fMRI, DTI… –New Algorithms Integrated through ITK Wrapping –Grid-Compatible Distributed Computation P41, MBIRN, fBIRN

National Alliance for Medical Image Computing 3D Slicer Draw on Orthogonal Planes Connectivity Tools Math Morphology Image Masking and Logical Operations Level Sets Provided by S. Pieper

National Alliance for Medical Image Computing Overview Introduction Core 1 Core 2 Core 3 Support Cores Slicer Demo

National Alliance for Medical Image Computing Core 3.1: Harvard, Dartmouth –Fronto-temporal connections –Cognitive and behavioral data Core 3.2: UCI, Toronto –Brain regions involving DLPFC –Clinical, cognitive, genetic data Core 3: Overview

National Alliance for Medical Image Computing Example R. Al-Hakim, J. Fallon Segmentation of Area 46 (not 51)

National Alliance for Medical Image Computing Overview Introduction Core 1 Core 2 Core 3 Support Cores Slicer Demo

National Alliance for Medical Image Computing Support Cores (# 4-7) Service, Training Dissemination Crucial Support for the Scientific and Engineering Enterprise Support Core PIs also have Strong Scientific Credentials Collaboration History through BIRN and ITK

National Alliance for Medical Image Computing Training

National Alliance for Medical Image Computing Dissemination: Events

National Alliance for Medical Image Computing Core 7: Management Operational Support –Process Definition –Communication and Coordination –Reporting –Project Management Proactive Management –Project Tracking and Oversight –Process Change Management –New DBP Planning

National Alliance for Medical Image Computing NA-MIC-Organization Structure

National Alliance for Medical Image Computing For More Information Information about Collaborations (NIH PA)

National Alliance for Medical Image Computing Overview Introduction Core 1 Core 2 Core 3 Support Cores Slicer Demo

National Alliance for Medical Image Computing For More Information Information about Collaborations (NIH PA)