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Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]]
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= NA-MIC Internal Collaborations =
  
(Updated 09/12/2006)
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This is a list of all collaborative projects within NA-MIC. These projects form the basis of the progress reports submitted to the NIH. These collaborations are between team members of the various [[Cores|cores]] of NA-MIC.
  
'''Objective:'''
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== Diffusion Image Analysis ==
  
We have developed a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. Our work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, non-global, non-uniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset.
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=== Fiber Tract Extraction and Analysis ===
  
'''Progress:'''
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Fiber_Tract_Statistics|Fiber Tract Statistics]] (Utah, UNC)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Diffusion_measures_alongs_fiber_tracts_of_the_cingulum_bundle|Diffusion measures alongs fiber tracts of the cingulum bundle]] (Harvard, MIT, UNC)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Clustering_of_anatomically_distinct_fiber_tracts|Clustering of anatomically distinct fiber tracts]] (Harvard, MIT)
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# [[Algorithm:GATech:Finsler_Active_Contour_DWI|Anisotropic Conformal Metrics for DTI Tractography]] (Georgia Tech, Harvard)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Corpus_Callosum_Fiber_Tractography_in_Schizophrenia|Corpus Callosum Fiber Tractography in Schizophrenia]] (Dartmouth, Harvard, MIT)
  
* We developed a multiscale representation of 3D surfaces using conformal mappings and spherical wavelets. We then learned a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. This novel multiscale shape prior was shown to encode more descriptive and localized shape variations than the Active Shape Models (ASM) prior for a given training set size. The results were published in [1] on a prostate dataset.
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=== Fractional Anisotropy Analysis ===
  
* We have replicated our results from [1] on the left caudate nucleus dataset from the Brockton dataset (Harvard, Core 3). Additionally, one of the nice application of our technique is the automatic discovery of uncorrelated shape variations in a dataset, at various scales. The visualization of resulting bands on the mean shape can in itself be interesting for shape analysis (see Figure) by indicating which surface patches co-vary across the training set. For example at scale 1, bands 1 and 2 indicate two uncorrelated shape processes in the caudate data that make sense anatomically: the variation of the head and of the body. It is also interesting that bands have compact spatial support, though this is not a constraint of our technique.
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Corpus_Callosum_Regional_FA_analysis_in_Schizophrenia|Corpus Callosum Regional FA analysis in Schizophrenia]] (Harvard, UNC, Dartmouth)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Fractional_Anisotropy_of_the_Corpus_Callosum_and_Anterior_Commissure|Fractional Anisotropy of the Corpus Callosum and Anterior Commissure]] (Harvard, MIT, Dartmouth)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Fractional_Anisotrophy_in_the_Uncinate_Fasciculus_in_Schizophrenia_and_Bipolar_I_Disorder--replication_and_extension_of_Kubicki_study|Fractional Anisotrophy in the Uncinate Fasciculus in Schizophrenia and Bipolar I Disorder--replication and extension of Kubicki study]] (Dartmouth, Harvard)
  
<div class="thumb tright"><div style="width: 182px">[[Image:Gatech_caudateBands.PNG|[[Image:180px-Gatech_caudateBands.PNG|Figure 1: 2 examples bands discovered by the prior color-coded on the mean shape of the 29 left caudates from the Harvard Brockton dataset. The color shows the cumulative value of the wavelet bases that belong to that band. Higher value (light-blue to red) areas represent surface locations with correlated variations across shapes]]]]<div class="thumbcaption"><div class="magnify" style="float: right">[[Image:Gatech_caudateBands.PNG|[[Image:magnify-clip.png|Enlarge]]]]</div>Figure 1: 2 examples bands discovered by the prior color-coded on the mean shape of the 29 left caudates from the Harvard Brockton dataset. The color shows the cumulative value of the wavelet bases that belong to that band. Higher value (light-blue to red) areas represent surface locations with correlated variations across shapes</div></div></div>
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=== Path of Interest Analysis ===
  
* ''' Segmentation'''<nowiki>: Based on our representation, we derived a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. In [2] we report results on the caudate nucleus in the Brockton dataset (Harvard, Core 3). Our validation shows that our algorithm is computationally efficient and outperforms the Active Shape Model (ASM) algorithm, by capturing finer shape details. </nowiki>
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Integrity_of_Fronto-Temporal_Circuitry_in_Schizophrenia_using_Path_of_Interest_Analysis|Integrity of Fronto-Temporal Circuitry in Schizophrenia using Path of Interest Analysis]] (Dartmouth, MGH, Isomics, Harvard)
  
'''Ongoing:'''
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=== Validation ===
  
* ''' Classification'''<nowiki>: We are collaborating with Martin Styner (UNC, Core 1) to include our shape features in the UNC shape analysis pipeline. We obtained interesting preliminary results that have been verified by Jim Levitt (Harvard PNL, Core 3). See </nowiki>[[NA-MIC/Projects/Structural/Shape_Analysis/Caudate_and_Corpus_Callosum|Caudate and Corpus Callosum Analysis]]. We have also discussed our results with Martin Styner during a UNC site visit (see [[Georgia_Tech_visit_to_UNC%2C_June_8-9|June 8-9, 2006, Georgia Tech visit to UNC: Shape Analysis Discussion]]). A scientific paper is being prepared with our results.
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Validation|DTI Validation]] (UCI, MGH, UNC, MIT)
* ''' ITK Filter'''<nowiki>: We are developing an ITK Filter for the Spherical wavelet transform (See </nowiki>[[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]])
 
  
'''References:'''
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=== Algorithm/Software Infrastructure ===
  
* [1] Nain D, Haker S, Bobick A, Tannenbaum A. Multiscale 3D Shape Analysis using Spherical Wavelets. Proc MICCAI, Oct 26-29 2005; p 459-467 [http://www.bme.gatech.edu/groups/minerva/publications/papers/nain.miccai2005.pdf [1]]
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/DTI_Software_and_Algorithm_Infrastructure|DTI Software/Algorithm Infrastructure]] (Utah, UNC)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Tensor_based_statistics|Tensor based statistics]] (Harvard, Utah)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Diffusion_tensor_image_filtering|Diffusion tensor image filtering]] (Utah, Harvard)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Non-rigid_EPI_Registration|Non-rigid EPI Registration]] (Harvard/MGH, Kitware, Dartmouth)
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# [[NA-MIC/Projects/Diffusion_Image_Analysis/Fiber_Tools_Slicer_Integration|Fiber Tools Integration with Slicer 3]] (UNC, GE, Isomics)
  
* [2] Nain D, Haker S, Bobick A, Tannenbaum A. Shape-driven 3D Segmentation using
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== Structural Image Analysis ==
  
Spherical Wavelets. Proc MICCAI, Oct 2-5, 2006. To Appear.
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=== Image Segmentation ===
  
'''Key Investigators:'''
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# [[Algorithm:GATech:Knowledge_Based_Bayesian_Segmentation|Knowledge-Based Bayesian Classification and Segmentation]] (Georgia Tech, Kitware)
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# [[NA-MIC/Projects/Structural/Segmentation/Interleaved_Segmentation_and_Registration|Brain Tissue Classification and Subparcellation of Brain Structures]] (Harvard, MIT, Kitware)
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# [[Algorithm:GATech:Rule_Based_Segmentation|Rule based segmentation: Striatum]] (Georgia Tech, Harvard, Isomics, Kitware)
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# [[Algorithm:GATech:Rule_Based_Segmentation|Rule based segmentation: DLPFC]] (Georgia Tech, UCI, Isomics, Kitware)
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# [[Algorithm:GATech:Multiscale_Shape_Segmentation|Multiscale Shape Segmentation Techniques]] (Georgia Tech, Harvard)
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# [[NA-MIC/Projects/Structural/Segmentation/Stochastic_Methods_for_Segmentation|Stochastic Methods for Segmentation]] (Georgia Tech)
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# [[Algorithm:GATech:Statistical_Segmentation_Slicer_2|Statistical/PDE methods for Segmentation]] (Georgia Tech)
  
* Georgia Tech: Delphine Nain, Aaron Bobick, Allen Tannenbaum, Yi Gao and Xavier Le Faucheur
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=== Image Registration ===
* Harvard SPL: Steve Haker
 
  
'''Collaborators'''
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# [[Algorithm:GATech:Optimal_Mass_Transport_Registration|Optimal Mass Transport for Registration]] (Georgia Tech, Harvard)
  
* Core 1: Martin Styner (UNC)
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=== Morphometric Measures and Shape Analysis ===
* Core 2: Jim Miller (GE), Luis Ibanez (Kitware)
 
* Core 3: James Levitt, Marc Niethammer, Sylvain Bouix, Martha Shenton (Harvard PNL)
 
  
'''Links:'''
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# [[NA-MIC/Projects/Structural/Shape_Analysis/Caudate_and_Corpus_Callosum|Shape Analysis for the caudate and corpus callosum data]] (Harvard, UNC, Georgia Tech, Dartmouth)
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# [[NA-MIC/Projects/Structural/Shape_Analysis/Hippocampus|Shape Analysis of the hippocampus]] (Dartmouth, UNC, Harvard)
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# [[Algorithm:GATech:Multiscale_Shape_Analysis|Multiscale Shape Analysis applied to Caudate and Hippocampus]] (Georgia Tech, Harvard, UNC)
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# [[NA-MIC/Projects/Structural/Shape_Analysis/Using_LONI_Pipeline|UNC Shape Analysis with LONI pipeline for clinical investigators]] (UNC, UCLA)
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# [[NA-MIC/Projects/Structural/Population_Studies|Population Studies]] (UNC, GE)
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# [[NA-MIC/Projects/Structural/Morphometric_Measures/Mild_Cognitive_Impairment|Multi-site morphometry in Mild Cognitive Impairment]] (UCI, mBIRN?)
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# [[NA-MIC/Projects/Structural/Morphometric_Measures/Schizophrenia/Muti-site_Morphometry|Multi-site morphometry in Schizophrenia]] (UCI, FBIRN)
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# [[NA-MIC/Projects/Structural/Shape_Analysis/Automated_shape_model_construction|Automated shape model construction]] (Utah, Harvard)
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# [[NA-MIC/Projects/Structural/Morphometric_Measures/Schizophrenia/Neural_Substrates_of_Apathy|Neural substrates of apathy in schizophrenia]] (Dartmouth, Isomics)
  
* [[NA-MIC/Projects/Structural/Shape_Analysis/Caudate_and_Corpus_Callosum|Caudate and Corpus Callosum Analysis]].
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== fMRI Analysis ==
* [[Georgia_Tech_visit_to_UNC%2C_June_8-9|June 8-9, 2006, Georgia Tech visit to UNC: Shape Analysis Discussion]]
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* [[NA-MIC/Projects/Structural/Shape_Analysis/Spherical_Wavelets_in_ITK|ITK Spherical Wavelet Transform Filter]]
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=== Functional Activation Analysis ===
* [[Algorithm:GATech#Multiscale_Shape_Analysis|Georgia Tech Summary Page]]
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# [[NA-MIC/Projects/fMRI_Analysis/Neural_Substrates_of_Working_Memory_in_Schizophrenia:_A_Parametric_3-Back_Study|Neural Substrates of Working Memory in Schizophrenia: A Parametric 3-Back Study]] (Dartmouth, Harvard)
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# [[NA-MIC/Projects/fMRI_Analysis/Brain_Activation_during_a_Continuous_Verbal_Encoding_and_Recognition_Task_in_Schizophrenia|Brain Activation during a Continuous Verbal Encoding and Recognition Task in Schizophrenia]] (Dartmouth, Harvard)
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# [[NA-MIC/Projects/fMRI_Analysis/Fronto-Temporal_Connectivity_in_Schizophrenia_during_Semantic_Memory|Fronto-Temporal Connectivity in Schizophrenia during Semantic Memory]] (Dartmouth, Harvard)
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# [[NA-MIC/Projects/fMRI_Analysis/Imaging_Phenotypes_in_Schizophrenics_and_Controls|Imaging Phenotypes in Schizophrenics and Controls]] (UCI, Toronto)
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# [[NA-MIC/Projects/fMRI_Analysis/Attentional_Circuits_in_Schizophrenia_as_revealed_by_fMRI_and_PET|Attentional Circuits in Schizophrenia as revealed by fMRI and PET]] (UCI)
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=== Algorithm and Software Infrastructure ===
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# [[NA-MIC/Projects/fMRI_Analysis/fMRI_Statistics_Software_Infrastructure|fMRI Statistics Software Infrastructure]] (GE, Isomics, Kitware, MIT)
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# [[NA-MIC/Projects/fMRI_Analysis/Spatial_Regularization_for_fMRI_Detection|Spatial Regularization for fMRI Detection]] (MIT, Harvard)
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# [[Algorithm:GATech:Conformal_Flattening_Registration|Conformal Flattening for fMRI Visualization]] (Georgia Tech, Harvard)
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== NA-MIC Kit ==
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=== NAMIC Software Process ===
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# [[NA-MIC/Projects/NA-MIC_Kit/CMake_-_NAMIC_Kit_Building|CMake - NAMIC Kit Building]] (Kitware)
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# [[NA-MIC/Projects/NA-MIC_Kit/CPack_-_NAMIC_Kit_Distribution|CPack - NAMIC Kit Distribution]] (Kitware)
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# [[NA-MIC/Projects/NA-MIC_Kit/Dart_2_and_CTest_-_Software_Quality|Dart 2 and CTest - Software Quality]] (GE, Kitware)
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=== Software Infrastructure ===
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# [[NA-MIC/Projects/NA-MIC_Kit/Slicer3|Slicer 3]] (Isomics, GE, Kitware, UCSD, UCLA)
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# [[NA-MIC/Projects/NA-MIC_Kit/Coordinate_Systems|Coordinate Systems]] (GE, Isomics)
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# [[NA-MIC/Projects/NA-MIC_Kit/IO_Unification|IO Unification]] (GE, Isomics)
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# [[NA-MIC/Projects/NA-MIC_Kit/Licenses_Unification|Licenses Unification]] (Kitware, Isomics)
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# [[NA-MIC/Projects/NA-MIC_Kit/Grid_Computing|Grid Computing]] (UCSD, UCLA, GE, Kitware, Isomics)
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# [[NA-MIC/Projects/NA-MIC_Kit/KWWidgets|KWWidgets]] (Kitware)
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# [[NA-MIC/Projects/NA-MIC_Kit/Execution_Model|Execution Model]] (GE)
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# [[NA-MIC/Projects/NA-MIC_Kit/MRML|MRML]] (Isomics, Kitware, GE)
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# [[NA-MIC/Projects/NA-MIC_Kit/Teem|Teem]] (Harvard/BWH)
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=== Training & Dissemination ===
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# [[NA-MIC/Projects/NA-MIC_Kit/Training_Material_and_Workshops_for_NA-MIC_Kit|Training Material and Workshops for NA-MIC Kit]] (Harvard/MGH, Harvard/BWH)
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# [[NA-MIC/Projects/NA-MIC_Kit/Dissemination|Dissemination for NA-MIC]] (Isomics, Kitware, Harvard)
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== Other Projects ==
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# [[Non_Rigid_Registration|Non-Rigid Registration]]
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= NA-MIC External Collaborations =
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This section describes all external collaborations with NA-MIC. Details for the primary funding mechanism for collaborating with NCBCs are provided [[Collaborator:Resources|here]].
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== PAR-05-063 Automated FE Mesh Development ==
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This project is a NCBC collaboration grant. Collaborators include Nicole Grosland, Vincent Magnotta, Steve Pieper, and Simon Warfield. The master page for this collaboration is [[NA-MIC_NCBC_Collaboration:Automated_FE_Mesh_Development|here]], while the rest of this section contains links to the specific active projects in this collaboration.
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=== Meshing Algorithms ===
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# [[Novel_Hexahedral_Meshing_Algorithms|Novel Hexahedral Meshing Algorithms]] (Iowa)
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# [[Hex_vs_Tet_Mesh_Comparisons|Hex vs Tet Mesh Comparisons]] (Iowa/Isomics/BWH)
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=== Automated Segmentation ===
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# [[Integration_of_Neural_Network_Algorithms|Integration of Neural Network Algorithms]] (Iowa)
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=== Image Registration ===
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# [[Evaluation_of_Inter-Modality_Registration]] (Iowa/Isomics)
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=== Validation ===
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# [[Validation_of_Defined_Regions_of_Interest_Using_Surface_Scanning]] (Iowa)
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# [[FE_Mesh_Validation]] (Iowa)

Latest revision as of 14:04, 18 December 2006

Home < NA

NA-MIC Internal Collaborations

This is a list of all collaborative projects within NA-MIC. These projects form the basis of the progress reports submitted to the NIH. These collaborations are between team members of the various cores of NA-MIC.

Diffusion Image Analysis

Fiber Tract Extraction and Analysis

  1. Fiber Tract Statistics (Utah, UNC)
  2. Diffusion measures alongs fiber tracts of the cingulum bundle (Harvard, MIT, UNC)
  3. Clustering of anatomically distinct fiber tracts (Harvard, MIT)
  4. Anisotropic Conformal Metrics for DTI Tractography (Georgia Tech, Harvard)
  5. Corpus Callosum Fiber Tractography in Schizophrenia (Dartmouth, Harvard, MIT)

Fractional Anisotropy Analysis

  1. Corpus Callosum Regional FA analysis in Schizophrenia (Harvard, UNC, Dartmouth)
  2. Fractional Anisotropy of the Corpus Callosum and Anterior Commissure (Harvard, MIT, Dartmouth)
  3. Fractional Anisotrophy in the Uncinate Fasciculus in Schizophrenia and Bipolar I Disorder--replication and extension of Kubicki study (Dartmouth, Harvard)

Path of Interest Analysis

  1. Integrity of Fronto-Temporal Circuitry in Schizophrenia using Path of Interest Analysis (Dartmouth, MGH, Isomics, Harvard)

Validation

  1. DTI Validation (UCI, MGH, UNC, MIT)

Algorithm/Software Infrastructure

  1. DTI Software/Algorithm Infrastructure (Utah, UNC)
  2. Tensor based statistics (Harvard, Utah)
  3. Diffusion tensor image filtering (Utah, Harvard)
  4. Non-rigid EPI Registration (Harvard/MGH, Kitware, Dartmouth)
  5. Fiber Tools Integration with Slicer 3 (UNC, GE, Isomics)

Structural Image Analysis

Image Segmentation

  1. Knowledge-Based Bayesian Classification and Segmentation (Georgia Tech, Kitware)
  2. Brain Tissue Classification and Subparcellation of Brain Structures (Harvard, MIT, Kitware)
  3. Rule based segmentation: Striatum (Georgia Tech, Harvard, Isomics, Kitware)
  4. Rule based segmentation: DLPFC (Georgia Tech, UCI, Isomics, Kitware)
  5. Multiscale Shape Segmentation Techniques (Georgia Tech, Harvard)
  6. Stochastic Methods for Segmentation (Georgia Tech)
  7. Statistical/PDE methods for Segmentation (Georgia Tech)

Image Registration

  1. Optimal Mass Transport for Registration (Georgia Tech, Harvard)

Morphometric Measures and Shape Analysis

  1. Shape Analysis for the caudate and corpus callosum data (Harvard, UNC, Georgia Tech, Dartmouth)
  2. Shape Analysis of the hippocampus (Dartmouth, UNC, Harvard)
  3. Multiscale Shape Analysis applied to Caudate and Hippocampus (Georgia Tech, Harvard, UNC)
  4. UNC Shape Analysis with LONI pipeline for clinical investigators (UNC, UCLA)
  5. Population Studies (UNC, GE)
  6. Multi-site morphometry in Mild Cognitive Impairment (UCI, mBIRN?)
  7. Multi-site morphometry in Schizophrenia (UCI, FBIRN)
  8. Automated shape model construction (Utah, Harvard)
  9. Neural substrates of apathy in schizophrenia (Dartmouth, Isomics)

fMRI Analysis

Functional Activation Analysis

  1. Neural Substrates of Working Memory in Schizophrenia: A Parametric 3-Back Study (Dartmouth, Harvard)
  2. Brain Activation during a Continuous Verbal Encoding and Recognition Task in Schizophrenia (Dartmouth, Harvard)
  3. Fronto-Temporal Connectivity in Schizophrenia during Semantic Memory (Dartmouth, Harvard)
  4. Imaging Phenotypes in Schizophrenics and Controls (UCI, Toronto)
  5. Attentional Circuits in Schizophrenia as revealed by fMRI and PET (UCI)

Algorithm and Software Infrastructure

  1. fMRI Statistics Software Infrastructure (GE, Isomics, Kitware, MIT)
  2. Spatial Regularization for fMRI Detection (MIT, Harvard)
  3. Conformal Flattening for fMRI Visualization (Georgia Tech, Harvard)

NA-MIC Kit

NAMIC Software Process

  1. CMake - NAMIC Kit Building (Kitware)
  2. CPack - NAMIC Kit Distribution (Kitware)
  3. Dart 2 and CTest - Software Quality (GE, Kitware)

Software Infrastructure

  1. Slicer 3 (Isomics, GE, Kitware, UCSD, UCLA)
  2. Coordinate Systems (GE, Isomics)
  3. IO Unification (GE, Isomics)
  4. Licenses Unification (Kitware, Isomics)
  5. Grid Computing (UCSD, UCLA, GE, Kitware, Isomics)
  6. KWWidgets (Kitware)
  7. Execution Model (GE)
  8. MRML (Isomics, Kitware, GE)
  9. Teem (Harvard/BWH)

Training & Dissemination

  1. Training Material and Workshops for NA-MIC Kit (Harvard/MGH, Harvard/BWH)
  2. Dissemination for NA-MIC (Isomics, Kitware, Harvard)

Other Projects

  1. Non-Rigid Registration

NA-MIC External Collaborations

This section describes all external collaborations with NA-MIC. Details for the primary funding mechanism for collaborating with NCBCs are provided here.

PAR-05-063 Automated FE Mesh Development

This project is a NCBC collaboration grant. Collaborators include Nicole Grosland, Vincent Magnotta, Steve Pieper, and Simon Warfield. The master page for this collaboration is here, while the rest of this section contains links to the specific active projects in this collaboration.

Meshing Algorithms

  1. Novel Hexahedral Meshing Algorithms (Iowa)
  2. Hex vs Tet Mesh Comparisons (Iowa/Isomics/BWH)

Automated Segmentation

  1. Integration of Neural Network Algorithms (Iowa)

Image Registration

  1. Evaluation_of_Inter-Modality_Registration (Iowa/Isomics)

Validation

  1. Validation_of_Defined_Regions_of_Interest_Using_Surface_Scanning (Iowa)
  2. FE_Mesh_Validation (Iowa)