Figure 2

Representative images of each step of the improved histological routine for a rhesus macaque femur. After obtaining the microscopic image, the 3D printed cone-shaped fiducial markers were identified as the conic cross-section of each histological image (A). The lengths of the minor and major axes were calculated by fitting an ellipse in the segmented data. The length of the minor axis was used to calculate the intersection points of the cut plane with the inertia axes-system of the individual cones, resulting in three defined points (one for each cone) in the CT data coordinate system spanning the in silico cutting plane (black) in (B). Subsequently, the CT data in that plane was extracted and used for multimodal registration with the histological data (C). The qualitative result of our workflow is illustrated in the chessboard overlay in (D). A precise match of in silico and histological sections is evident by no visible distortions on the edges of the checkerboards. In (E) the sublimely matched in silico slice with the binarized histology image mask is depicted. Here, black pixels correspond to an accurate matching, while red and green pixels represent false negative and false positive samples, respectively.