The suitable implant for each previously designated implant recipient site was selected by using the cross-sectional images.
The sectional images were further analysed using ImageJ software (National Institutes of Health, Bethesda, MD, USA) and calibrated with respect to mineral density using the mouse incisor as a calibrator.
At the core laboratory, volume-rendering images, curved multi-planar reformation (MPR) images, interactive oblique MPR images, thin maximum intensity projection (MIP) images and cross-sectional images were prepared using the images reconstructed at each study center.
The film thickness of the electrochemical growth of the V2O5 thin films was measured using the cross-sectional SEM images (inset of Fig. 2a c), with thicknesses of 321, 621, and 1047 nm for the deposition times of 20, 40, and 60 s, respectively.
The thickness of the films was estimated using the cross-sectional FESEM image.
We measured all cerebral volumes on T1-W 3D images by using the cross-sectional version of SIENA (structural image evaluation using normalization of brain atrophy) software, SIENAX (part of FSL 5.0: http://www.fmrib.ox.ac.uk/fsl/), a tool used to estimate the global brain volume normalized for head size.
Many studies investigating body composition using cross-sectional images have used this approach particularly when estimating visceral and subcutaneous adipose quantities with good success [13, 14].
Brain parenchyma volumes were measured on T1-W images by using the cross-sectional version of the SIENA software, SIENAX [19], [20], part of FSL.
Each sample was cut into three pieces using a diamond saw and then scanned to obtain the cross sectional images using a desktop flatbed scanner.
Histological cross-sections were then compared with the corresponding OCT cross-sectional images using the right carotid artery bifurcation as the common landmark for localisation.
