Summer ITKv4 ClinicalGroupMeetingNotes

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

Overlap and Similarity

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

ITKv4 Features

• GPU
• Registration framework

(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)

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:

• ?

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.
• 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)