View source for ITK Release 4/A2D2 Projects/Physics-Based Non-rigid Registration

= Goals =
To develop an ITK implementation of physics-based Non-Rigid Registration (NRR) for Image- Guided Surgery (IGS) that will satisfy the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time to less than one minute. 

= Motivation =


The benefits to the ITK community are at least two-fold. First, as a stand-alone software we will provide a computationally efficient registration method that accounts for tissue properties and that approximates sparse deformation. Second, through ITK integration into other IGS toolkits, NRR will be part of open-source systems like 3D-Slicer and IGSTK, and commercial systems like BrainLab.

= Methodology =
Our methodology is based on the separation of the NRR method into two parts: a regular part, block matching that utilizes the GPU, and an irregular part, a Finite Element solver that is mapped to multi-core processors

= Deliverable =


'''Feature Point Selection''' filter as ''itk::MaskFeaturePointSelection3D'' derived from ''itk::ImageToMeshFilter''

Input:

* floating image as `itk::Image`

* mask image as `itk::Image`

Output:

* list of selected points as ''itk::PointSet''

For each point we store:

* image coordinates

* real coordinates

* tensor


'''Block Matching filter''' as ''itk::BlockMatching3D''

Input:

* floating image as ''itk::Image''

* fixed image as ''itk::Image''

* list of selected points (output of ''itk::MaskFeaturePointSelection3D'') as ''itk::PointSet''

Output:

* displacement field as ''itk::PointSet''

For each point we store:

* image coordinates

* real coordinates

* tensor

* confidence

* displacement

* correlation


'''FEMScatteredDataPointSetToImageFilter'''

Description:

FEM-based approximation to interpolation filter. The scattered point set is approximated by a piece-wise linear function regularized by a linear elastic biomechanical model. The approximation error is reduced iteratively to reach interpolation accuracy. This filter takes a point set, mesh and material as inputs and outputs a deformation field. The following figures show the flow chart and the inheritance diagram, respectively.

https://lh3.googleusercontent.com/-AwciP2fboJs/Tl-wklhdCvI/AAAAAAAAABA/RNHamvIG-xM/FEMScatteredDataPointSetToImageFilter.jpg


'''RobustSolver'''

Description:

A robust solver against outliers. This solver is developed based on the interface of LinearSystemWrapper, which can be implemented by vnl or PETSc.

https://lh6.googleusercontent.com/-nhWx9OQUBAU/Tl-zW7ffskI/AAAAAAAAABE/M4pK15Mt-oY/RobustSolver.jpg

= Team =
* Nikos Chrisochoides  ( ODU )  
* Andriy Kot  ( ODU ) 
* Yixun Liu ( ODU )
* Michel Audette ( ODU )
* Andinet Enquobahrie ( Kitware )