Elastic registration of 3D cartilage surfaces from MR image data for detecting local changes in cartilage thickness.

The objective of this work was to develop and validate a computational method for the registration (matching) of 3D cartilage plates from MR image data sets. The technique tracks local cartilage thickness changes over time. A 3D elastic registration technique was applied that identifies corresponding points of the bone-cartilage interface in MR data sets of 3D-reconstructed cartilage plates. In a first rigid preregistration step, the surfaces are aligned, using the principal axes decomposition to correct for different joint positions and orientations in the MR scanner. In a second step, the surfaces are deformed elastically, based on geometric surface features, until they are sufficiently similar to identify corresponding surface points. The method was validated against artificially corrupted cartilage surfaces and MR data obtained from in vivo and in vitro compression experiments. The in vivo reproducibility was tested on patellar data sets of volunteers, with repositioning of the joint in between replicate acquisitions.