Diagnostic validity of early proximal caries detection using near-infrared imaging technology on 3D range data of posterior teeth

Objectives This in vitro study analysed potential of early proximal caries detection using 3D range data of teeth consisting of near-infrared reflection images at 850 nm (NIRR). Materials and methods Two hundred fifty healthy and carious permanent human teeth were arranged pairwise, examined with bitewing radiography (BWR) and NIRR and validated with micro-computed tomography. NIRR findings were evaluated from buccal, lingual and occlusal (trilateral) views according to yes/no decisions about presence of caries. Reliability assessments included kappa statistics and revealed high agreement for both methods. Statistical analysis included cross tabulation and calculation of sensitivity, specificity and AUC. Results Underestimation of caries was 24.8% for NIRR and 26.4% for BWR. Overestimation was 10.4% for occlusal NIRR and 0% for BWR. Trilateral NIRR had overall accuracy of 64.8%, overestimation of 15.6% and underestimation of 19.6%. NIRR and BWR showed high specificity and low sensitivity for proximal caries detection. Conclusions NIRR achieved diagnostic results comparable to BWR. Trilateral NIRR assessments overestimated presence of proximal caries, revealing stronger sensitivity for initial caries detection than BWR. Clinical relevance NIRR provided valid complement to BWR as diagnostic instrument. Investigation from multiple angles did not substantially improve proximal caries detection with NIRR.

Outdoor Autonomous Navigation Utilizing Proximity Points of 3D Pointcloud

In this paper, an autonomous navigation method that utilizes proximity points of 3D range data is proposed for use in mobile robots. Some useful geometric properties of proximity points are derived, and a computationally efficient algorithm for extracting such points from 3D pointclouds is presented. Unlike previously proposed keypoints, the proximity point does not require any computationally expensive analysis of the local curvature, and is useful for detecting reliable keypoints in an environment where objects with definite curvatures such as edges and flat surfaces are scarce. Moreover, a particle-filter-based self-localization method that uses proximity points for a similarity measure of observation is presented. The proposed method was implemented in a real mobile robot system, and its performance was tested in an outdoor experiment conducted during Nakanoshima Challenge 2019.