Summer ITKv4 ClinicalGroupMeetingNotes: Difference between revisions

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(Created page with "== Lesion Sizing Toolkit == Inputs: dicom Outputs: measures of volumes, segmentations * Already in ITK as an external module. Contract is to reimplement with ITKv4 and distribu...")
 
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Data: 60 datasets. Chest CT scans 1mm resolution. 200mb each. MIDAS?  Store as DICOM?  Automatically download using CTest.
Data: 60 datasets. Chest CT scans 1mm resolution. 200mb each. MIDAS?  Store as DICOM?  Automatically download using CTest.


##3D Real-Time Physics-Based Non-Rigid Registration for Image Guided Neurosurgery (PBMNRRegistration)
== 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.
The following is a rough pipeline of the method with proposed classes.
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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 ==


Data:  
Data:  

Revision as of 16:39, 27 June 2011

Lesion Sizing Toolkit

Inputs: dicom Outputs: measures of volumes, segmentations

  • Already in ITK as an external module. Contract is to reimplement with ITKv4 and distribute.
  • Using spatial objects as inputs and outputs
  • Should some of these algorithms be migrated into ITK proper? (e.g. enhanced canny edge detection)

What support it 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.

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.

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. (segmentation -> mesh gen -> registration -> petsc -> generate image (deformation field)) Inputs: a mask, a mesh

1) FeaturePointSelection3dFilter(mask, fixed image): start with this filter 2) BlockMatching3Dfilter(fixed, moving, metrics,feature points) -- GPU, similar to penn fem registration classes, maybe metric plug in 3) PBMSolver(displacement vector, mesh) --petsc dependence 4) ImageWarp--already in ITK

Outputs: deformation field, transformed image(s)

Gaps:

  • Mesh generation, tetmesh reader / converter: Biomesh3D and bridge to ITK?
  • ITK Mesh
  • Self-updating transform object
  • Integration of solver
  • MPI with ITK?

What support is needed?

  • CMake integration w/ petsc (uses MPI). Build / distribution
  • Interface w/ FEM guys, registration & GPU guys


ITK Algorithms for Analyzing Time-Varying Shape with Application to Longitudinal Heart Modeling

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.