Summer ITKv4 ClinicalGroupMeetingNotes: Difference between revisions

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== 3D Real-Time Physics-Based Non-Rigid Registration for Image Guided Neurosurgery (PBMNRRegistration) ==
== Overlap and Similarity ==
The following is a rough pipeline of the method with proposed classes.
* Level of integration questions.
* Bridges to 3rd party libs
* Distribution questions: How to build/package with 3rd party libs. How to distribute data.


Inputs: a segmentation mask, a mesh
== ITKv4 Features ==
Outputs: deformation field, transformed image(s)
* GPU
* Registration framework


1) FeaturePointSelection3dFilter:  No dependencies.  Plan to start implementation with this filter.  
== 3D Real-Time Physics-Based Non-Rigid Registration for Image Guided Neurosurgery ==
2) 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.
The following is a rough pipeline of the method with proposed classes.
3) PBMSolver: PETSc dependence
<br><br>
4) ImageWarp: Already in ITK
<b>Contributions:</b> New filters, classes.  Application?<br>
<b>Inputs:</b> a segmentation mask, a mesh
<b>Outputs:</b> deformation field, transformed image(s)<br>
# 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


<b>What support is needed?</b>
* CMake integration w/ PETSc and MPI.  Build / distribution issues.
* Further discussion and collaboration with the FEM, registration, and GPU groups.


Gaps:
<b>Gaps:</b>
* Mesh generation. Tetmesh reader / converter?  Use Biomesh3D and bridge to ITK?
* Mesh generation. Tetmesh reader / converter?  Use Biomesh3D and bridge to ITK?
* Self-updating transform object
* Self-updating transform object
* PETSc & MPI within an ITK filter?
* PETSc & MPI within an ITK filter?


What support is needed?
<b>Data:</b>
* CMake integration w/ PETSc and MPI.  Build / distribution issues.
* Sample dataset for testing.
* Further discussion and collaboration with the FEM, registration, and GPU groups.


Data:
<b>Distribution:</b>
* ?
External module?


== Lesion Sizing Toolkit ==
== Lesion Sizing Toolkit ==
Inputs: DICOM
<b>Contributions:</b> Functioning toolkit and application.  Possibly new ITK filters classes.  Data.
Outputs: Lesion volume measurements and segmentations.
* Already in ITK as an external module.  Contract is to port to use ITKv4 and distribute.
* Using spatial objects as inputs and outputs <br>
<b>Inputs:</b> DICOM
<b>Outputs:</b> Lesion volume measurements and segmentations.<br>


* Already in ITK as an external module.  Contract is to reimplement with ITKv4 and distribute.
<b>What support is needed?</b>
* 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


* Using spatial objects as inputs and outputs
<b>Gaps:</b>
* Should some of these algorithms be migrated into ITK proper? (e.g. enhanced canny edge detection)
* Representing measures as a concept in ITK
* Annotations / metadata


What support it needed?
<b>Data:</b> 60 datasets. Chest CT scans 1mm resolution. 200mb each. MIDAS? Store as DICOM?  Automatically download using CTest.
* Does ITK want a tighter integration of these classes, and in this same form?  Does this cover more general concepts useful to other groups.


Gaps:
<b>Distribution:</b> Currently external module.  More integration?
* 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 ==
<b>Contributions:</b> New ITK module (particle system), filters, classes.<br>
<b>Inputs:</b> Segmentations
<b>Outputs:</b> Point sets<br>


* Uses the core of an existing code base built from ITK: [http://www.nitrc.org/projects/shapeworks ShapeWorks NITRC Repository]
* Port significant portions to ITKv4
* New ParticleSystem module.  New ITK filter process objects.
* Procrustes registration
* Generic infrastructure for point-based surface representations
* Cross-sectional and longitudinal analysis


== ITK Algorithms for Analyzing Time-Varying Shape with Application to Longitudinal Heart Modeling ==
<b>What support is needed?</b>
* Logistics of integration and distribution, including data.
* Future: support for mesh representation, GPU


Data:  
<b>Data:</b>
* 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)
* 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
* Need IRB to release image data


Gaps:  
<b>Gaps:</b>
* Multivariate stats.
* Multivariate stats:  Bridge to R for complex statistical analysis without going to file system. Only implement what is needed for within ITK algorithms.
* Bridge to R for complex statistical analysis without going to file system.
 
<b>Distribution:</b>
ITK Module.  Test applications.  Integration with third party applications (ShapeWorks)

Latest revision as of 19:41, 27 June 2011

Overlap and Similarity

  • Level of integration questions.
  • Bridges to 3rd party libs
  • Distribution questions: How to build/package with 3rd party libs. How to distribute data.

ITKv4 Features

  • GPU
  • Registration framework

3D Real-Time Physics-Based Non-Rigid Registration for Image Guided Neurosurgery

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)

  1. FeaturePointSelection3dFilter: No dependencies. Plan to start implementation with this filter.
  2. 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.
  3. PBMSolver: PETSc dependence
  4. 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:

  • Sample dataset for testing.

Distribution: External module?

Lesion Sizing Toolkit

Contributions: Functioning toolkit and application. 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
  • Annotations / metadata

Data: 60 datasets. Chest CT scans 1mm resolution. 200mb each. MIDAS? Store as DICOM? Automatically download using CTest.

Distribution: Currently external module. More integration?

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

  • Uses the core of an existing code base built from ITK: ShapeWorks NITRC Repository
  • Port significant portions to ITKv4
  • New ParticleSystem module. New ITK filter process objects.
  • Procrustes registration
  • Generic infrastructure for point-based surface representations
  • Cross-sectional and longitudinal analysis

What support is needed?

  • Logistics of integration and distribution, including data.
  • Future: support for mesh representation, GPU

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.

Distribution: ITK Module. Test applications. Integration with third party applications (ShapeWorks)

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