TubeTK/Events/2010.07.26: Difference between revisions

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= Andinet =
= Topics =
* Primary goal: Data from Duke for BWH
* Dashboards auto update?
* Accomplishments
** tubetk/CMake/DashboardScripts tubetk/CMake/CTestCustom...
** Attend NAMIC AHM
* Batch Processing
** Determine what is necessary to record data sent to OpenIGTLink from VectorVision system
** Python vs BatchMake vs Any
*** Define data workflow and software architecture
* Slicer
*** Begin implementation
** TubeNet Viewer
*** Product: powerpoint presentation: 5 slides
** Slicer load .tre
* Near term (August 1)
** Slicer Loadable Module
** Install VV at Duke
* Registration
** Determine if we can get US data from Duke machine
** Speckle in ultrasound registration
** Write IJ article
** Model-based deformation field interpolation
*** Cite grant proposal in article
** Fluid deformation (Marc)
* Medium term (1.5 months, August 15)
** Registration metrics based on ultrasound probe orientation
** Investigate simulation of ultrasound from MR/CT (Talk to Stephen First :) )
* Segmentation
** Code review of vessel segmentation method from Stephen
** Unit test VTree code
*** 3D
*** 2D
** Automated vessel tree extraction
*** Using spatial prior
*** Seed selection
** Automated distinguishing arteries from veins based on spatial prior
* Atlas formation
** Retinal data
*** Email from UIowa (still waiting)
** Brain data
*** Vessel extractions from Liz
** Port pipeline to VTree
 
= Status =


= Patrick =
== Patrick ==
* Primary goal: Bump and dent identification on IC images
* Primary goal: Bump and dent identification on IC images
* Accomplishments
* Accomplishments
** Traveled to SSRL to view the acquisition and meet with Greg and Mike.
** Modified the GenerateFeatures application to handle the input of arbitrary feature images
** Using the previous features and Casey's new patch-based features, was able to achieve 95% pixel level accuracy in Weka and 23/25 defects found with 0 false positives in image space (after morphology).
** Explore new features
** Explore new features
*** z-score values from three different mean/stdDev joint histograms: add, subtract, and unchanged
*** evaluate a variety of standard deviations for intensity and ridge computations
*** evaluate a variety of standard deviations for intensity and ridge computations
** New centerline method (skeletonization)
* Near Term (Aug 2)
** GenerateFeaturesForWeka
** Receiving code to simulate the tomography directly on GDS Layers
* Near Term (Aug 1)
** Compute dot-product between line (hessian) tangent and normal directions in ES and GDS images
** Get registered data from Greg
** Subselect features
** compute dot-product between line (hessian) tangent and normal directions in ES and GDS images
** write program that goes from Weka output to image and computes TPR/FPR scores on that image
** Collaborate with Casey
*** Choose classification scheme
*** Implement in C++ or python - in tubetk
**** Use neuralnets / parzenWindowing in ITK
*** Subselect features
** Product: ~ 5 slides / report to USC illustrating path chosen, strengths, and weaknesses.
** Product: ~ 5 slides / report to USC illustrating path chosen, strengths, and weaknesses.
*** Real-world tests / workflow
*** Real-world tests / workflow
Line 39: Line 48:
**** i.e., do we need to insert modifications for training on every slice / acquisition / ?
**** i.e., do we need to insert modifications for training on every slice / acquisition / ?
**** Normalizing for inter-acquisition (or inter-slice) variations?
**** Normalizing for inter-acquisition (or inter-slice) variations?
** Go to Synchrotron
** Work with new collaborator at Kitware.
* Medium term (1 months, August 15)
* Medium term (August 9)
** Delivery and education
** Delivery and education
** Can we get better in simulation?
** Can we get better in simulation?
** chip-to-chip matching
** connectivity analysis
== Casey ==
* Primary goal: Compare populations of vascular networks
* Near term (Aug 2)
** Feature extraction
*** Patch-based features (max, median, quantiles)
*** Scales / neighborhood
** Feature research
*** Width estimate
**** Not the same as Gaussian blur
*** New patch features
*** Location of local max in ridgeness
*** Subsample centerlines
*** Optimal match filter
** Classifiers
*** Comparison
*** Implementation for transfer to USC
*** Hierarchy (Good/bad.  If bad, then add/sub.)
* Medium term (Aug 9)
** Connectivity analysis
** Connectivity analysis
** chip-to-chip comparison


= Casey =
== Andinet ==
* Primary goal: Compare populations of vascular networks
* Primary goal: Data from Duke for BWH
* Near term (0.5, Aug 1)
* Accomplishments
** Collaborate with Patrick
** Data from Duke
*** Feature extraction
*** Contacted several folks to gather information ( we had questions regarding the machine at Duke) and check status.
**** Patch-based features (max, median, quantiles)
**** BrainLab: Contacted Pratik. He is working on getting us VV license
**** Scales / neighborhood
**** Duke: Contacted Tanya and learned that SD-5000  ultrasound machine is not integrated with the BrainLab system. The machine is used to acquire ultrasound data independently.
*** Feature research
**** Aloka: Contacted John Walsh at Aloka and learned that SD-5000 is very old model and doesn't come with research interface
**** Width estimate from Stephen (concern, time)
*** Based upon the conversation I had with you, may be we should probably look into saving data off the BrainLab system itself not bother with the SD-5000.
**** Location of local max in ridgeness
** Write IJ article
**** Subsample centerlines
*** Made progress writing the IJ article. Hua helped me a lot generating results using synthetic data. We have now a solid outline and some write up in most of the sections
**** Optimal match filter
*** You can also access the tex, bib, etc files in my Work directory: Work/Andinet/TensorIJ
*** Classifiers
* Near term (August 2)
**** Comparison
** IJ Article
**** Implementation for transfer to USC
*** Move article to TubeTK/Documentation/2010.TensorIJ
**** Hierarchy (Good/bad.  If bad, then add/sub.)
*** Add more texts, figures and results and clean it up more.
** Data for Retinas
*** Put together self-contained source code tree containing the classes that we will submit with this paper.
* Medium term (1 months, Aug 15)
*** Refer to TubeTK
** Review previous processing pipeline with Stephen
*** Cite grant proposal in article
** Research on methods for comparing spatial graphs / adjacency matrices
** Install VV at Duke
** Begin Port and test existing adjacency code
* Medium term (August 9)
** Process retinal data
** Complete port and test of existing adjacency code
*** Prepare IJ article


= Hua =
== Hua ==
* Primary goal: ultrasound image processing
* Primary goal: ultrasound image processing
* Accomplished
* Accomplished
** Verify Andinet's code: add tests and help with IJ publication
** Correct a bug in itkAnisotropicHybridDiffusionImageFilter
*** Creating tests (sin pattern with known derivatives)
** prepared figures for Andinet's Insight Journal paper.
* Near term (August 1)
** Improve code coverage for uncovered filters under Application/CLI/** Increase coverage of TubeTK
** Increase coverage of TubeTK
* Near term (August 2)
** Update registration code
** Update registration code
** Begin investigation of registration metrics that depend on ultrasound probe orientation
** Begin investigation of registration metrics that depend on ultrasound probe orientation
*** Get data from InnerOptic
*** Get data from InnerOptic
**** Design phantom or use something from InnerOptic
**** Discuss with InnerOptic
**** CIRS Phantom
**** http://www.insight-journal.org/midas/item/view/2206
**** http://www.insight-journal.org/midas/item/view/2206
**** http://www.insight-journal.org/midas/item/view/117
**** http://www.insight-journal.org/midas/item/view/117
* Medium term (1.5 months
* Medium term (August 9)
** Investigate use of speckle in ultrasound registration
 
** Model-based deformation field interpolation
[[Category:TubeTK Events and Meetings|2010.07.26]]
** 2D-3D registration (data)
** Simulating ultrasound from MR/CT

Latest revision as of 18:45, 26 July 2013

Topics

  • Dashboards auto update?
    • tubetk/CMake/DashboardScripts tubetk/CMake/CTestCustom...
  • Batch Processing
    • Python vs BatchMake vs Any
  • Slicer
    • TubeNet Viewer
    • Slicer load .tre
    • Slicer Loadable Module
  • Registration
    • Speckle in ultrasound registration
    • Model-based deformation field interpolation
    • Fluid deformation (Marc)
    • Registration metrics based on ultrasound probe orientation
  • Segmentation
    • Unit test VTree code
      • 3D
      • 2D
    • Automated vessel tree extraction
      • Using spatial prior
      • Seed selection
    • Automated distinguishing arteries from veins based on spatial prior
  • Atlas formation
    • Retinal data
      • Email from UIowa (still waiting)
    • Brain data
      • Vessel extractions from Liz
    • Port pipeline to VTree

Status

Patrick

  • Primary goal: Bump and dent identification on IC images
  • Accomplishments
    • Traveled to SSRL to view the acquisition and meet with Greg and Mike.
    • Modified the GenerateFeatures application to handle the input of arbitrary feature images
    • Using the previous features and Casey's new patch-based features, was able to achieve 95% pixel level accuracy in Weka and 23/25 defects found with 0 false positives in image space (after morphology).
    • Explore new features
      • evaluate a variety of standard deviations for intensity and ridge computations
  • Near Term (Aug 2)
    • Receiving code to simulate the tomography directly on GDS Layers
    • Compute dot-product between line (hessian) tangent and normal directions in ES and GDS images
    • Subselect features
    • Product: ~ 5 slides / report to USC illustrating path chosen, strengths, and weaknesses.
      • Real-world tests / workflow
      • Does a trained classifier work on other layers?
      • Does a trained classifier work on other acquisitions?
        • i.e., do we need to insert modifications for training on every slice / acquisition / ?
        • Normalizing for inter-acquisition (or inter-slice) variations?
    • Work with new collaborator at Kitware.
  • Medium term (August 9)
    • Delivery and education
    • Can we get better in simulation?
    • chip-to-chip matching
    • connectivity analysis

Casey

  • Primary goal: Compare populations of vascular networks
  • Near term (Aug 2)
    • Feature extraction
      • Patch-based features (max, median, quantiles)
      • Scales / neighborhood
    • Feature research
      • Width estimate
        • Not the same as Gaussian blur
      • New patch features
      • Location of local max in ridgeness
      • Subsample centerlines
      • Optimal match filter
    • Classifiers
      • Comparison
      • Implementation for transfer to USC
      • Hierarchy (Good/bad. If bad, then add/sub.)
  • Medium term (Aug 9)
    • Connectivity analysis
    • chip-to-chip comparison

Andinet

  • Primary goal: Data from Duke for BWH
  • Accomplishments
    • Data from Duke
      • Contacted several folks to gather information ( we had questions regarding the machine at Duke) and check status.
        • BrainLab: Contacted Pratik. He is working on getting us VV license
        • Duke: Contacted Tanya and learned that SD-5000 ultrasound machine is not integrated with the BrainLab system. The machine is used to acquire ultrasound data independently.
        • Aloka: Contacted John Walsh at Aloka and learned that SD-5000 is very old model and doesn't come with research interface
      • Based upon the conversation I had with you, may be we should probably look into saving data off the BrainLab system itself not bother with the SD-5000.
    • Write IJ article
      • Made progress writing the IJ article. Hua helped me a lot generating results using synthetic data. We have now a solid outline and some write up in most of the sections
      • You can also access the tex, bib, etc files in my Work directory: Work/Andinet/TensorIJ
  • Near term (August 2)
    • IJ Article
      • Move article to TubeTK/Documentation/2010.TensorIJ
      • Add more texts, figures and results and clean it up more.
      • Put together self-contained source code tree containing the classes that we will submit with this paper.
      • Refer to TubeTK
      • Cite grant proposal in article
    • Install VV at Duke
  • Medium term (August 9)

Hua

  • Primary goal: ultrasound image processing
  • Accomplished
    • Correct a bug in itkAnisotropicHybridDiffusionImageFilter
    • prepared figures for Andinet's Insight Journal paper.
    • Improve code coverage for uncovered filters under Application/CLI/** Increase coverage of TubeTK
  • Near term (August 2)
  • Medium term (August 9)