TubeTK/Events/2010.07.12: Difference between revisions

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= Andinet =
= Andinet =
* Primary goal: Data from Duke for BWH
* Primary goal: Data from Duke for BWH
* Near term (2 weeks, July 2nd)
* Accomplishments
** Attend NAMIC AHM
** Attend NAMIC AHM
** Determine what is necessary to record data sent to OpenIGTLink from VectorVision system
** Determine what is necessary to record data sent to OpenIGTLink from VectorVision system
Line 8: Line 7:
*** Begin implementation
*** Begin implementation
*** Product: powerpoint presentation: 5 slides
*** Product: powerpoint presentation: 5 slides
* Medium term (1.5 months, August 1)
* Near term (August 1)
** Investigate simulation of ultrasound from MR/CT
** Install VV at Duke
** Complete IJ article on tensor diffusion
** Determine if we can get US data from Duke machine
** Write IJ article
*** Cite grant proposal in article
*** Cite grant proposal in article
* Medium term (1.5 months, August 15)
** Investigate simulation of ultrasound from MR/CT (Talk to Stephen First :) )
** Code review of vessel segmentation method from Stephen


= Patrick =
= Patrick =
* Primary goal: Bump and dent identification on IC images
* Primary goal: Bump and dent identification on IC images
* Near term (2 weeks, July 2nd)
* Accomplishments
** Explore new features
** Explore new features
*** z-score values from three different mean/stdDev joint histograms: add, subtract, and unchanged
*** z-score values from three different mean/stdDev joint histograms: add, subtract, and unchanged
*** write program that goes from weiki output to image and computes TPR/FPR scores on that image
*** evaluate a variety of standard deviations for intensity and ridge computations
*** evaluate a variety of standard deviations for intensity and ridge computations
*** compute dot-product between line (hessian) tangent and normal directions in ES and GDS images
** New centerline method (skeletonization)
*** Product: ~ 5 slides to USC illustrating path chosen, strengths, and weaknesses.
** GenerateFeaturesForWeka
* Medium term (1.5 months, August 1)
* Near Term (Aug 1)
** Report to USC
** Get registered data from Greg
** 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.
*** 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?
** Go to Synchrotron
* Medium term (1 months, August 15)
** Delivery and education
** Can we get better in simulation?
** Connectivity analysis


= Casey =
= Casey =
* Primary goal: Compare populations of vascular networks
* Primary goal: Compare populations of vascular networks
* Near term (2 weeks, July 2nd)
* Near term (0.5, Aug 1)
** Collaborate with Patrick
*** Feature extraction
**** Patch-based features (max, median, quantiles)
**** Scales / neighborhood
*** Feature research
**** Width estimate from Stephen (concern, time)
**** 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.)
** Data for Retinas
* Medium term (1 months, Aug 15)
** Review previous processing pipeline with Stephen
** Review previous processing pipeline with Stephen
** Research on methods for comparing spatial graphs / adjacency matrices
** Research on methods for comparing spatial graphs / adjacency matrices
** Begin Port and test existing adjacency code
** Begin Port and test existing adjacency code
* Medium term (1.5 months)
** Process retinal data
** Process retinal data
** Complete port and test of existing adjacency code
** Complete port and test of existing adjacency code
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= Hua =
= Hua =
* Primary goal: ultrasound image processing
* Primary goal: ultrasound image processing
* Near term (2 weeks, July 2nd)
* Accomplished
** Verify Andinet's code: add tests and help with IJ publication
** Verify Andinet's code: add tests and help with IJ publication
*** Creating tests (sin pattern with known derivatives)
*** Creating tests (sin pattern with known derivatives)
*** Done by next wednesday (June 23)
* Near term (August 1)
*** Choose Michel vs BWH
** Increase coverage of TubeTK
** Update registration code
** Begin investigation of registration metrics that depend on ultrasound probe orientation
*** 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/117
* Medium term (1.5 months
* Medium term (1.5 months
** Investigate use of speckle in ultrasound registration
** Investigate use of speckle in ultrasound registration
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** 2D-3D registration (data)
** 2D-3D registration (data)
** Simulating ultrasound from MR/CT
** Simulating ultrasound from MR/CT
[[Category:TubeTK Events and Meetings|2010.07.12]]

Latest revision as of 18:45, 26 July 2013

Andinet

  • Primary goal: Data from Duke for BWH
  • Accomplishments
    • Attend NAMIC AHM
    • Determine what is necessary to record data sent to OpenIGTLink from VectorVision system
      • Define data workflow and software architecture
      • Begin implementation
      • Product: powerpoint presentation: 5 slides
  • Near term (August 1)
    • Install VV at Duke
    • Determine if we can get US data from Duke machine
    • Write IJ article
      • Cite grant proposal in article
  • Medium term (1.5 months, August 15)
    • Investigate simulation of ultrasound from MR/CT (Talk to Stephen First :) )
    • Code review of vessel segmentation method from Stephen

Patrick

  • Primary goal: Bump and dent identification on IC images
  • Accomplishments
    • 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
    • New centerline method (skeletonization)
    • GenerateFeaturesForWeka
  • Near Term (Aug 1)
    • Get registered data from Greg
    • 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.
      • 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?
    • Go to Synchrotron
  • Medium term (1 months, August 15)
    • Delivery and education
    • Can we get better in simulation?
    • Connectivity analysis

Casey

  • Primary goal: Compare populations of vascular networks
  • Near term (0.5, Aug 1)
    • Collaborate with Patrick
      • Feature extraction
        • Patch-based features (max, median, quantiles)
        • Scales / neighborhood
      • Feature research
        • Width estimate from Stephen (concern, time)
        • 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.)
    • Data for Retinas
  • Medium term (1 months, Aug 15)
    • Review previous processing pipeline with Stephen
    • Research on methods for comparing spatial graphs / adjacency matrices
    • Begin Port and test existing adjacency code
    • Process retinal data
    • Complete port and test of existing adjacency code
      • Prepare IJ article

Hua

  • Primary goal: ultrasound image processing
  • Accomplished
    • Verify Andinet's code: add tests and help with IJ publication
      • Creating tests (sin pattern with known derivatives)
  • Near term (August 1)
  • Medium term (1.5 months
    • Investigate use of speckle in ultrasound registration
    • Model-based deformation field interpolation
    • 2D-3D registration (data)
    • Simulating ultrasound from MR/CT
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