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UNC Algorithms page

Diffusion Tensor Imaging

Quantitative Analysis of Fiber Tract Bundles

See at the end of this page/further below for old content, please delete old content after update.

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Description - Publications - Software

Population Analysis from Deformable Registration


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Description - Publications - Software

Shape Analysis of Brain Structures Across Groups

Shape analysis has become of increasing relevance to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures. This project focuses on developing novel methodology and a comprehensive set of tools for the computation of 3D structural statistical shape analysis. There are several open problems in this area, ranging from multi-object analysis, enhanced shape correspondence to statistical analysis of shape with clinical covariates.

UNC Shape Analysis Framework using SPHARM-PDM

The UNC shape analysis is based on an analysis framework of objects with spherical topology, described mainly by sampled spherical harmonics SPHARM-PDM. The input of the shape analysis framework is a set of binary segmentations of a single brain structure, such as the hippocampus or caudate. These segmentations are converted into a shape description (SPHARM) with correspondence and analyzed via Hotelling T^2 two sample metric. More...

New:

  • First version of Shape Analysis Toolset available as part of UNC Neurolib open source (download) , this is to be added to the NAMIC toolkit.
  • Toolset distribution contains open data for other researcher to evaluate novel shape analysis enhancements
  • Slicer 3 modules for individual tools in the UNC Shape Analysis Toolset completed
  • Slicer 3 module for whole shape analysis pipeline in progress (based on BatchMake and distributed computing using Condor)
  • New shape analysis related papers:
    • 2 submissions to the Main MICCAI 2007 conference
    • Styner M, Xu SC, El-Sayed M, Gerig G, Correspondence Evaluation in Local Shape Analysis and Structural Subdivision, IEEE Symposium on Biomedical Imaging ISBI 2007, in print
    • Zhou C, Park DC, Styner M, Wang YM, ROI Constrained Statistical Surface Morphometry, IEEE Symposium on Biomedical Imaging ISBI 2007, in print
    • Nain D, Styner M, Niethammer M, Levitt JJ, Shenton ME, Gerig G, Bobick A, Tannenbaum A, Statistical Shape Analysis of Brain Structures Using Spherical Wavelets, IEEE Symposium on Biomedical Imaging ISBI 2007, in print
    • M. Styner, I. Oguz, S. Xu, D. Pantazis, and G. Gerig. Statistical group differences in anatomical shape analysis using hotelling T2 metric. Proc SPIE Medical Imaging Conference, in print, 2007.
    • C Cascio, M Styner, RG Smith, M Poe, G Gerig, H Hazlett, M Jomier, R Bammer, J Piven, Reduced relationship to cortical white matter revealed by tractography-based segmentation of the corpus callosum in yound children with developmental delay, Am J Psychiatry, 2006, (163) 2157-2163, December.

Description - Publications - Software

UNCShape CaudatePval MICCAI06.png

Population Based Correspondence

We are developing methodology to automatically find dense point correspondences between a collection of polygonal genus 0 meshes. The advantage of this method is independence from indivisual templates, as well as enhanced modeling properties. The method is based on minimizing a cost function that describes the goodness of correspondence. Apart from a cost function derived from the description length of the model, we also employ a cost function working with arbitrary local features. We extended the original methods to use surface curvature measurements, which are independent to differences of object aligment. More...

New:

  • Software available as part of UNC Neurolib open source (website)
  • Evaluation on lateral ventricles, hippocampi, caudates, striatum, femural bone. Outperforms standard MDL on complex structures.
  • Submission to MICCAI 2007 conference
  • Tobias Heimann, I. Oguz, I. Wolf, M. Styner, HP. Meinzer. Implementing the Automatic Generation of 3D Statistical Shape Models with ITK. Accepted to MICCAI 2006 Open Source Workshop. More...

Description - Publications - Software

Local Statistical Analysis via Permutation Tests

We have further developed a set of statistical testing methods that allow the analysis of local shape differences using the Hotelling T 2 two sample metric. Permutatioin tests are employed for the computation of statistical p-values, both raw and corrected for multiple comparisons. Resulting significance maps are easily visualized. Additional visualization of the group tests are provided via mean difference magnitude and vector maps, as well as maps of the group covariance information. Ongoing research focuses on incorporating covariates such as clinical scores into the testing scheme. More...

New:

  • Available as part of Shape Analysis Toolset in UNC Neurolib open source (download).
  • M. Styner, I. Oguz, S. Xu, C. Brechbuehler, D. Pantazis, J. Levitt, M. Shenton, G. Gerig. Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM. Accepted to MICCAI 2006 Open Source Workshop. More...


Description - Publications - Software

Collaborations with other groups in NAMIC

  • Algorithms:
    • Shape Analysis
      • Joint pipeline I/O formulation and development with Kitware (Brad Davis, Jim Miller) and MIT (Polina Golland)
      • Use of UNC statistical analysis for spherical wavelet shape with GeorgiaTech (Delphine Nain) and Utah (Tom Fletcher)
      • Use of UNC statistical analysis for combined multi-object correspondence establishment with Utah (Josh Cates, Tom Fletcher)
    • DTI
      • Statistics of tensors and noise in diffusion weighted imaging with Utah (Tom Fletcher)
  • Clinical:
    • Collaboration with Harvard on shape analysis and DTI analysis.

Old content, delete after full update

Nov 30, 2004

DTI: Quantitative analysis of fiber bundles

Components of FiberViewer Project

    Input: Sets of streamlines from tractography:
      ITK polyline format with DTI attributes
    Clustering of sets of streamlines to sets of
      strong fiber bundles using various curve
      distance metrics
    Parametrization of sets of lines and
      reparametrization for equidistant sampling
      with arc-length
    Calculation of local geometric properties of
      streamlines (Frenet frame, curvature, torsion)
    Attributing streamlines at each sample point
      with DTI measurements (ADC, FA, lambda1..3,
      ev. whole tensor) via trilinear interpolation
    Calculation of DTI statistics within cross-
      sections along fiber tracts after selection
      of coordinate origin
    Write statistics (DTI properties as a function
      of arclength) to a text file for statistical
      analysis.
    Output: Processed, cleaned and clustered fiber
      bundles (ITK polyline format) / Statistics
      of DTI properties per selected bundle

Software

  • Algorithms written in ITK. GUI of prototype software written in QT (FiberViewer software). Prototype software tested in clinical studies at UNC. Validation tests with repeated DTI of same subject (6 cases).
  • Additionally available: ITK compatible fibertracking prototype tool FiberTracking to be used to study overlap/dissimilarity with other tools already available to NA-MIC: Functionality: reads raw MRI-DT data (6 direction Basser scheme), fiber tracking based on user-selected source and regions (S. Mori scheme), display of fibertracts and volumetric data, output: sets of streamlines in ITK polyline format attributedwith DTI properties and display parameteres (radiusof tubes, local color, etc.).

DTI Training Tools

DTI Training Tools (Downloadable in zip package File:DTI-Training-Tools.zip)

  • Glyphs - displays FA slices and tensor field
  • Fiber - simplistic tractography from single voxel
  • Conn - display of Riemannian flow from voxel
  • MRIWatcher - displays a set of MRI volumes simultaneously. MRTWatcher can also overlay segmentation mask.

The manual for DTI Training Tools is included in zip file. Source code for the programs is available from UNC NeuroLib.

Recent Activities

  • UNC has developed a DTIFiberClass, which is now available as part of ITK
  • UNC has initiated the discussion for a standard format within NAMIC of representing DTI Tensor data and DTI Fibers
  • All software is available for download via anonymous download from our CVS server
pserver:anonymous@demeter.ia.unc.edu . Dashboard and Testing procedures have been installed and are operational.


Plans

  • Feasibility tests on DTI data from NAMIC clinical partners
  • DTI standardization issues (AHM SLC and follow-up)
  • Evaluation of Slicer integration

Long term

  • DTI Fiber shape representation tools
  • Correspondence via fiber bundles (shape, parametrization)
  • Fiber clustering via Normalized Cuts (ITK filter)

Relationship to other NA-MIC partners

       DTI preprocessing (smoothing, interpolation):
           MGH, Utah: Improve quality of raw DTI
           data, Resampling DTI including tensor
           re-orientation and full-tensor interpolation
       DTI tensor statistics using Lie Group analysis:
           Utah (Tom Fletcher), will replace the
            simple averaging of FA, ADC, lambda1..3
            as shown in "Averaging" step above
       DTI tensor calculation, tractography, combined
           display: Slicer, DoDTI (C.-F. Westin):
           Processing of DTI to get fiber tracts of
           interest for subsequent FiberViewer analysis
       DTI atlas: probabilistic DTI atlas of normal
           controls (MGH): To be used as reference
           DTI atlas of normal controls
       DTI annotated fiber tract atlas-template:
           M. Farlow: To be used to calculate
           fiber bundle properties for each annonated
           tract, to serve as refrence template for
           geometry and location of bundles as well
           as for DTI properties as a function of
           bundles.
       DTI clinical data schizophrenia: M. Shenton