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** Reconstruction baseed on the raw data | ** Reconstruction baseed on the raw data | ||
** Modify theoretical model based on observations | ** Modify theoretical model based on observations | ||
** | ** "Final" picture of proton from synthesis of multiple experiments and theoretical models | ||
* Phase space distributions | |||
** Use imaging techniques(e.g tesselation) | |||
** 10^6 -10^9 experiments | |||
** View distributions, projections, cuts, features | |||
** Compare distributions | |||
** Interpolate refine distributions for simulations | |||
** With ODU | |||
*** Tesselated representation | |||
*** compact memory-efficient representations | |||
*** Efficient interpolation/refinement for MC simulations | |||
*** Visualize the gamma ray points that were detected by the detector + the density of energy | |||
* Proton Structure: | |||
** Imaging for vizualitation of subnuclear system | |||
** Image concept for relativistic quantum system | |||
** Synthetic image from theory and multiple experiments | |||
** Spatial size, internal motion of quarks | |||
** Tesselated representation | |||
== Ron Kikinis == | |||
* 3D Slicer | |||
* Browser based versions | |||
** ohif.org | |||
** openanatomy.org | |||
* SlicerAstro | |||
** Use of Slicer3D in astronomy | |||
* Punzo et al 2015 | |||
== Neurosurgery == | |||
* In the past doctors would infer where the problem is by the symptoms. They would then open the brain and see if they were right | |||
* Now: Brain organization -> functional connectivity | |||
* Functional MRI measures blood flow | |||
* Diffusion Tensor Imaging the only method for imaging tensors | |||
* Combine fMRI with MEG or fMRI with MRI | |||
* VR to prepare for operation | |||
* AR to help annotate points of interest on the brain | |||
##Steve Pieper - New software - Keep using the best software we have - Open source - Reproducible science - 3D Slicer with - Python - Tensorflow - Numpy, pandas, scipy… - Wrapper API - Extensions marketplace - VR Support - Remote Rendering - Jupyter Notebook support - OHIF Viewer - Browser based medical image viewer - VTK.js - Crowds-cure.org - GPU Segmentation (Grow cut algorithm) | |||
== Tina Kapur == | |||
* Discourse Forum | |||
* Project Week Event | |||
* projectweek.na-mic.org | |||
== Andriy Fedorov == | |||
* “Your source code is your data”, NVIDIA CEO | |||
** For reproducibility for example | |||
* National Cancer Institutr Quantitative Imaging Network | |||
** Goal: Transalte quantitative imaging methods and algorithms as clinical decision support tools into clinical utility | |||
* DICOM includes metadata that can help to interpret images | |||
** Unique identifiers | |||
** Helps to query your data | |||
** TCIA (Cancer Imaging Archive) :Collection of medical images | |||
* NCI Cancer Research Data Commons | |||
Revision as of 12:24, 20 August 2019
CNF Workshop
- 08/19/19 Presentations
Nikos Chrisochoides
- Leverage from computational methods from medical imaging for processing phase space distributions in Nuclear Femtography
- Enable next generation process simulations
- Bring jobs to Virginia
- “Usefulness of Useless Knowledge” by Flexner
Bob McKeown
- Femtography 2019 ML & Revealing the internal structure of Nucelon & Nuclei
- See pic JLab Mission
- Nuclear Femtography
- High luminosity
- Polarized beams and targets
- Sophisticated detector systems
- Nature publications
- Ultrafast Nucleons in Asymmetic Nuclei
- …
- Virginia Center for Nyclear Femtography
- 7/14 joint lab/university initiatives funded
- Proposed JLab electron Ion Collider (see pic)
- EIC Users Group (see pic)
- EICUG 2019
- Current Status and Path forward of EIC (see pic
- JLab has electron collider, NY Brookhaven has ion collider
- Both need to construct the other half
Gail Dodge
- Partnership between ODU and JLab in 90’s
- 12 tenure track faculty
- 6 JLab professors
- ODU faculty intellectual leadership in research programs in JLab
- Bring together scientists from different fields
- ODU has hired ~6 data science faculty
- Need help to learn how to involve people from different disciplines
David Richards
- “Understanding the Glue That Binds Us All: The Next QCD Frontier in Nuclear Physics”
- See slide 6 for those that submitted proposals
- Synergy across fields
- Astrophysics
- Machine Learning
- Call for proposal late September
- External Evaluation Committee
- CNF Symposium at ODU early 2020
Christian Weiss
- Imaging technologies in computation
- Subnuclear systems
- Scales
- Scattering experiments
- Workflow inmeasurements
- Tesselation
- Scales
- Organisms- Cells
- Molecular - Atoms
- Nuclear - Subnuclear
- Mission: Explore subnuclear systems
- Strong interaction : quarks,gluons
- Understand proton neutron as emergent phenomena
- Interest
- Basic building blocks of matter
- nuclear structure and reactions, nuclear energy
- Subnuclear systems
- Unusual dynamical system
- Relativity: Energy = mass, conversion processes. Proton is ‘cauldron’ filled with radiation energy and matter/antimatter
- Only average properties are measurable: densities,correlations
- Scattering experiments
- Electrons collide on protons
- Scatterings are gathered from detectors
- JLab 12GeV accelerators
- Information Recorded:
- Distribution based on type and momentum -> Phase space distributions
- The “expression” of proton’s internal structure
- 10^6 - 10^9 experiments in JLab
- Workflow: Measurements
- Theory: Model of proton structure (parameters that need to be verified experimentally)
- Predicitions for scattering probabilities
- Phase space distributions (meeting ground between theory and experiments)
- Scattering Experiments -> Raw Data
- Reconstruction baseed on the raw data
- Modify theoretical model based on observations
- "Final" picture of proton from synthesis of multiple experiments and theoretical models
- Phase space distributions
- Use imaging techniques(e.g tesselation)
- 10^6 -10^9 experiments
- View distributions, projections, cuts, features
- Compare distributions
- Interpolate refine distributions for simulations
- With ODU
- Tesselated representation
- compact memory-efficient representations
- Efficient interpolation/refinement for MC simulations
- Visualize the gamma ray points that were detected by the detector + the density of energy
- Proton Structure:
- Imaging for vizualitation of subnuclear system
- Image concept for relativistic quantum system
- Synthetic image from theory and multiple experiments
- Spatial size, internal motion of quarks
- Tesselated representation
Ron Kikinis
- 3D Slicer
- Browser based versions
- ohif.org
- openanatomy.org
- SlicerAstro
- Use of Slicer3D in astronomy
- Punzo et al 2015
Neurosurgery
- In the past doctors would infer where the problem is by the symptoms. They would then open the brain and see if they were right
- Now: Brain organization -> functional connectivity
- Functional MRI measures blood flow
- Diffusion Tensor Imaging the only method for imaging tensors
- Combine fMRI with MEG or fMRI with MRI
- VR to prepare for operation
- AR to help annotate points of interest on the brain
- Steve Pieper - New software - Keep using the best software we have - Open source - Reproducible science - 3D Slicer with - Python - Tensorflow - Numpy, pandas, scipy… - Wrapper API - Extensions marketplace - VR Support - Remote Rendering - Jupyter Notebook support - OHIF Viewer - Browser based medical image viewer - VTK.js - Crowds-cure.org - GPU Segmentation (Grow cut algorithm)
Tina Kapur
- Discourse Forum
- Project Week Event
- projectweek.na-mic.org
Andriy Fedorov
- “Your source code is your data”, NVIDIA CEO
- For reproducibility for example
- National Cancer Institutr Quantitative Imaging Network
- Goal: Transalte quantitative imaging methods and algorithms as clinical decision support tools into clinical utility
- DICOM includes metadata that can help to interpret images
- Unique identifiers
- Helps to query your data
- TCIA (Cancer Imaging Archive) :Collection of medical images
- NCI Cancer Research Data Commons