METHODOLOGY: Jaw sections containing 67 teeth (86 roots) were collected from nine fresh, unclaimed bodies that were due for cremation. Imaging was carried out to detect AP lesions using film and digital PR with a centred view (FP and DP groups); film and digital PR combining central with 10˚ mesially and distally angled (parallax) views (FPS and DPS groups). All specimens underwent histopathological examination to confirm the diagnosis of AP. Sensitivity, specificity and predictive values of PR were analysed using rater mean (n = 5). Receiver operating characteristics (ROC) analysis was carried out.

RESULTS: Sensitivity was 0.16, 0.37, 0.27 and 0.38 for FP, FPS, DP and DPS, respectively. Both FP and FPS had specificity and positive predictive values of 1.0, whilst DP and DPS had specificity and positive predictive values of 0.99. Negative predictive value was 0.36, 0.43, 0.39 and 0.44 for FP, FPS, DP and DPS, respectively. Area under the curve (AUC) for the various imaging methods was 0.562 (FP), 0.629 (DP), 0.685 (FPS), 0.6880 (DPS).

METHODOLOGY: Jaw sections containing 67 teeth (86 roots) were collected from unclaimed bodies due for cremation. Imaging was carried out to detect AP by digital PR with a central view (DP group), digital PR combining central with 10˚ mesially and distally angled (parallax) views (DPS group) and CBCT scans. All specimens underwent histopathological examination to confirm the diagnosis of AP. Sensitivity, specificity and predictive values of PR and CBCT were analysed using rater mean (n = 5). Receiver-operating characteristic (ROC) analysis was carried out.

RESULTS: Sensitivity was 0.27, 0.38 and 0.89 for DP, DPS and CBCT scans, respectively. CBCT had specificity and positive predictive value of 1.0 whilst DP and DPS had specificity and positive predictive value of 0.99. The negative predictive value was 0.39, 0.44 and 0.81 for DP, DPS and CBCT scans, respectively. Area under the curve (AUC) for the various imaging methods was 0.629 (DP), 0.688 (DPS), and 0.943 (CBCT).

METHODS: In this study a novel system named Ceph-X is developed to computerize the manual tasks of orthodontics during cephalometric measurements. Ceph-X is developed by using image processing techniques with three main models: enhancements X-ray image model, locating landmark model, and computation model. Ceph-X was then evaluated by using X-ray images of 30 subjects (male and female) obtained from University of Malaya hospital. Three orthodontics specialists were involved in the evaluation of accuracy to avoid intra examiner error, and performance for Ceph-X, and 20 orthodontics specialists were involved in the evaluation of the usability, and user satisfaction for Ceph-X by using the SUS approach.

RESULTS: Statistical analysis for the comparison between the manual and automatic cephalometric approaches showed that Ceph-X achieved a great accuracy approximately 96.6%, with an acceptable errors variation approximately less than 0.5 mm, and 1°. Results showed that Ceph-X increased the specialist performance, and minimized the processing time to obtain cephalometric measurements of human skull. Furthermore, SUS analysis approach showed that Ceph-X has an excellent usability user's feedback.