The aim of this study was the registration of digitized thin 2D sections of mouse vertebrae and tibiae used for histomorphometry of trabecular bone structure into 3D micro computed tomography (μCT) datasets of the samples from which the sections were prepared. Intensity-based and segmentation-based registrations (SegRegs) of 2D sections and 3D μCT datasets were applied. As the 2D sections were deformed during their preparation, affine registration for the vertebrae was used instead of rigid registration. Tibiae sections were additionally cut on the distal end, which subsequently undergone more deformation so that elastic registration was necessary. The Jaccard distance was used as registration quality measure. The quality of intensity-based registrations and SegRegs was practically equal, although precision errors of the elastic registration of segmentation masks in tibiae were lower, while those in vertebrae were lower for the intensity-based registration. Results of SegReg significantly depended on the segmentation of the μCT datasets. Accuracy errors were reduced from approximately 64% to 42% when applying affine instead of rigid transformations for the vertebrae and from about 43% to 24% when using B-spline instead of rigid transformations for the tibiae. Accuracy errors can also be caused by the difference in spatial resolution between the thin sections (pixel size: 7.25 μm) and the μCT data (voxel size: 15 μm). In the vertebrae, average deformations amounted to a 6.7% shortening along the direction of sectioning and a 4% extension along the perpendicular direction corresponding to 0.13-0.17 mm. Maximum offsets in the mouse tibiae were 0.16 mm on average.
Keywords: 2D–3D image registration; deformation quantification; histological sections; trabecular structure; μCT.