Automated 3D–2D registration of X-ray microcomputed tomography with histological sections for dental implants in bone using chamfer matching and simulated annealing. (September 2015)

• Record Type: Journal Article
• Authors: Becker, Kathrin; Stauber, Martin; Schwarz, Frank; Beißbarth, Tim
• Is Part Of: Computerized medical imaging and graphics. Volume 44(2015)
• Page Start: 62
• Page End: 68
• Publication Date: 2015-09
• Subjects: I10 -- C65; Image registration -- Micro-computed tomography -- Histology -- Osseointegration -- Dental implants -- Histomorphometry; Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnosis, Radioscopic -- Data processing -- Periodicals; Diagnostic Imaging -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Diagnostic imaging; Periodicals; Electronic journals; Electronic journals; 616.0754
• DOI: 10.1016/j.compmedimag.2015.04.005
• Languages: English
• ISSNs: 0895-6111

Abstract

Abstract : Graphical abstract: Abstract : Highlights: We developed a novel method for automated 3D–2D registration of microCT and histology. We used the model of dental implant biopsies and found high agreement among the registered specimens. We directly compared the bone to implant contact (BIC) using the registered samples. We found significant positive association for the BIC measurements. Metal artifacts increased automated BIC measurements systematically. Abstract: We propose a novel 3D–2D registration approach for micro-computed tomography ( μ CT) and histology (HI), constructed for dental implant biopsies, that finds the position and normal vector of the oblique slice from μ CT 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 μ CT 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 μ CT were significant positively correlated with HI (median 0.65, 1.–3. Qu.: 0.59–0.72) between μ CT 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 μ CT may become a valid alternative to assess osseointegration in three dimensions.