TubeTK/Events/2010.06.14: Difference between revisions
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[[Category:TubeTK Events and Meetings|2010.06.14]] |
Latest revision as of 18:45, 26 July 2013
Andinet
- Primary goal: Data from Duke for BWH
- Near term (2 weeks, July 2nd)
- 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
- Medium term (1.5 months, August 1)
- Investigate simulation of ultrasound from MR/CT
- Complete IJ article on tensor diffusion
- Cite grant proposal in article
Patrick
- Primary goal: Bump and dent identification on IC images
- Near term (2 weeks, July 2nd)
- Explore new features
- 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
- compute dot-product between line (hessian) tangent and normal directions in ES and GDS images
- Product: ~ 5 slides to USC illustrating path chosen, strengths, and weaknesses.
- Explore new features
- Medium term (1.5 months, August 1)
- Report to USC
Casey
- Primary goal: Compare populations of vascular networks
- Near term (2 weeks, July 2nd)
- Review previous processing pipeline with Stephen
- Research on methods for comparing spatial graphs / adjacency matrices
- Begin Port and test existing adjacency code
- Medium term (1.5 months)
- Process retinal data
- Complete port and test of existing adjacency code
- Prepare IJ article
Hua
- Primary goal: ultrasound image processing
- Near term (2 weeks, July 2nd)
- Verify Andinet's code: add tests and help with IJ publication
- Creating tests (sin pattern with known derivatives)
- Done by next wednesday (June 23)
- Choose Michel vs BWH
- Verify Andinet's code: add tests and help with IJ publication
- 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