Enabling ParaView Interaction with ITK and Slicer

Collaboration on Computational Anatomy with Johns Hopkins Center for Imaging Science

A joint project by Johns Hopkins University's Center for Imaging Science, under Michael Miller, and Kitware, under Will Schroeder, is leading to new functionality in ParaView, to facilitate its use by JHU in order to empower its Computational Anatomy research. This blog entry documents on-going work on this project, which promises to facilitate the interactive use and visualization of results of the ITK classes for the medical imaging community at large, further potentiating their broad applicability and usefulness.

JHU CIS research emphasizes probabilistic anatomical atlases, including many structures of the brain, which encodes population shape statistics, for both surfaces and image sub-volumes representing anatomical structures. ParaView, which is already the platform of choice at JHU CIS for visualization, will also be relied upon by this group to manage its sophisticated image analysis, which characterizes shape variation in the population on the basis of Large Deformation Diffeomorphic Metric Mapping (LDDMM), by which one can establish correspondences between equivalent points in anatomically defined coordinates, and therefore statistical measurements determined from them, for a set of surfaces or segmented volumes of comparable structures.

In addition to being able to trigger ITK processing via VTK plug-ins that run on ParaView, an important component of this project is the management of a scene based on the notion of a scene graph as well as on the MRML standard, as developed under Slicer. The implication of treating anatomy as a scene graph is that this approach allows independent computations on, and effective visualization of, many anatomically distinct structures that comprise an atlas...