Summer ITKv4 ClinicalGroupMeetingNotes: Difference between revisions
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The following is a rough pipeline of the method with proposed classes. | The following is a rough pipeline of the method with proposed classes. | ||
<br><br> | <br><br> | ||
<b>Contributions:</b> New filters, classes. Application? | |||
<b>Inputs:</b> a segmentation mask, a mesh<br> | <b>Inputs:</b> a segmentation mask, a mesh<br> | ||
<b>Outputs:</b> deformation field, transformed image(s)<br> | <b>Outputs:</b> deformation field, transformed image(s)<br> | ||
# FeaturePointSelection3dFilter: No dependencies. Plan to start implementation with this filter. | # FeaturePointSelection3dFilter: No dependencies. Plan to start implementation with this filter. | ||
# BlockMatching3Dfilter: Similar to Penn FEM registration classes? Perhaps only need to implement a new metric? Plan to use the GPU infrastructure, but also have a non GPU version. | # BlockMatching3Dfilter: Similar to Penn FEM registration classes? Perhaps only need to implement a new metric? Plan to use the GPU infrastructure, but also have a non GPU version. | ||
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== Lesion Sizing Toolkit == | == Lesion Sizing Toolkit == | ||
<b>Contributions:</b> Functioning toolkit. Possibly new ITK filters classes. Data. | <b>Contributions:</b> Functioning toolkit. Possibly new ITK filters classes. Data. | ||
* Already in ITK as an external module. Contract is to port to use ITKv4 and distribute. | * Already in ITK as an external module. Contract is to port to use ITKv4 and distribute. | ||
* Using spatial objects as inputs and outputs | * Using spatial objects as inputs and outputs | ||
<b>Inputs:</b> DICOM | |||
<b>Outputs:</b> Lesion volume measurements and segmentations.<br> | |||
<b>What support is needed?</b> | <b>What support is needed?</b> | ||
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== ITK Algorithms for Analyzing Time-Varying Shape with Application to Longitudinal Heart Modeling == | == ITK Algorithms for Analyzing Time-Varying Shape with Application to Longitudinal Heart Modeling == | ||
<b>Contributions:</b> New ITK module (particle system), filters, classes. | |||
<b>Inputs:</b> Segmentations | <b>Inputs:</b> Segmentations | ||
<b>Outputs:</b> Point sets<br> | <b>Outputs:</b> Point sets<br> | ||
* Existing code base mostly ITK | * Existing code base mostly ITK | ||
* Port significant portions to ITKv4 | * Port significant portions to ITKv4 | ||
Revision as of 17:24, 27 June 2011
3D Real-Time Physics-Based Non-Rigid Registration for Image Guided Neurosurgery (PBMNRRegistration)
The following is a rough pipeline of the method with proposed classes.
Contributions: New filters, classes. Application?
Inputs: a segmentation mask, a mesh
Outputs: deformation field, transformed image(s)
- FeaturePointSelection3dFilter: No dependencies. Plan to start implementation with this filter.
- BlockMatching3Dfilter: Similar to Penn FEM registration classes? Perhaps only need to implement a new metric? Plan to use the GPU infrastructure, but also have a non GPU version.
- PBMSolver: PETSc dependence
- ImageWarp: Already in ITK
What support is needed?
- CMake integration w/ PETSc and MPI. Build / distribution issues.
- Further discussion and collaboration with the FEM, registration, and GPU groups.
Gaps:
- Mesh generation. Tetmesh reader / converter? Use Biomesh3D and bridge to ITK?
- Self-updating transform object
- PETSc & MPI within an ITK filter?
Data:
- ?
Lesion Sizing Toolkit
Contributions: Functioning toolkit. Possibly new ITK filters classes. Data.
- Already in ITK as an external module. Contract is to port to use ITKv4 and distribute.
- Using spatial objects as inputs and outputs
Inputs: DICOM
Outputs: Lesion volume measurements and segmentations.
What support is needed?
- Does ITK want a tighter integration of these classes, and in this same form? Does this cover more general concepts useful to other groups. e.g. Enhanced canny edge detection
Gaps:
- Representing measures as a concept in ITK
Data: 60 datasets. Chest CT scans 1mm resolution. 200mb each. MIDAS? Store as DICOM? Automatically download using CTest.
ITK Algorithms for Analyzing Time-Varying Shape with Application to Longitudinal Heart Modeling
Contributions: New ITK module (particle system), filters, classes.
Inputs: Segmentations
Outputs: Point sets
- Existing code base mostly ITK
- Port significant portions to ITKv4
- New ParticleSystem module. New ITK filter process objects.
What support is needed?
- Logistics of integration and distribution, including data.
Data:
- 25 longitudinal cardiac DE-MRI (1.25mm in-plane, 2.5mm thick) with segmentations of the left atrium. 2-4 datapoints each (pre ablation, 3mo, 6mo, 1 year)
- Need IRB to release image data
Gaps:
- Multivariate stats: Bridge to R for complex statistical analysis without going to file system. Only implement what is needed for within ITK algorithms.
