We propose a novel 3D–2D registration approach for micro-computed tomography (μCT) and histology (HI), constructed for dental implant biopsies, that finds the position and normal vector of the oblique slice from μCT that corresponds to HI. During image pre-processing, the implants and the bone tissue are segmented using a combination of thresholding, morphological filters and component labeling. After this, chamfer matching is employed to register the implant edges and fine registration of the bone tissues is achieved using simulated annealing. The method was tested on n =10 biopsies, obtained at 20 weeks after non-submerged healing in the canine mandible. The specimens were scanned with μCT 100 and processed for hard tissue sectioning. After registration, we assessed the agreement of bone to implant contact (BIC) using automated and manual measurements. Statistical analysis was conducted to test the agreement of the BIC measurements in the registered samples. Registration was successful for all specimens and agreement of the respective binary images was high (median: 0.90, 1.–3. Qu.: 0.89–0.91). Direct comparison of BIC yielded that automated (median 0.82, 1.–3. Qu.: 0.75–0.85) and manual (median 0.61, 1.–3. Qu.: 0.52–0.67) measures from μCT were significant positively correlated with HI (median 0.65, 1.–3. Qu.: 0.59–0.72) between μCT and HI groups (manual: R 2 =0.87, automated: R 2 =0.75, p <0.001). The results show that this method yields promising results and that μCT may become a valid alternative to assess osseointegration in three dimensions. 
Automated 3D–2D registration of X-ray microcomputed tomography with histological sections for dental implants in bone using chamfer matching and simulated annealing