Slicer3:DTMRI:GeneralDiffusionFramework

Demian Wasserman, Raul San Jose, Lauren O'Donnell

The goal is the define the basic design and data structure specifications to support general diffusion models in the slicer like two tensor diffusion models and higher order spherical harmonics tensors.

Initial development draft. Authors: Lauren, Demian, Raul

Redesign of MRLM

The generalization to general diffusion data models comes through a superclass that generalizes the original behaviour of vtkDiffusionTensorVolumeNode as described in the original design ([1] and [2]) This new class, vtkDiffusionImageVolumeNode, is a child of vtkMRMLTensorVolumeNode and abstract the behaviour related to diffusion imaging. The main members are:

• ID to the Diffusion Weighted Volume Node
• ID to the Baseline Image Volume Node
• ID to the Mask Image Volume Node.

Specifications to encapsulate General Diffusion Data into vtkImageData

Slicer 3 intrinsic image data representation is a vtkImageData class. This implies important limitations, namely

• The design is strictly 3D: the data is supposed to be arranged in a 3D grid and there is not possibilities for further extensions
• A specific set of point data attributes are allowed: Scalars, Normals,