Abstract: A computer-implemented method and system of digitally segmenting teeth in a digital model comprises generating a panoramic image from a 3D digital model of a patient's dentition, labeling, using a first trained neural network, the panoramic image to provide a labeled panoramic image, mapping the labeled panoramic image to corresponding coarse digital surface triangle labels in the 3D digital model to provide a labeled 3D digital model, and segmenting the labeled 3D digital model to provide a segmented 3D digital model. A computer-implemented method and system of generating a panoramic image comprises determining, using a trained neural network, digital tooth bounding region(s) corresponding to digital teeth from a 2D depth map of a patient's dentition, connecting digital tooth bounding region(s) by a spline, determining sampled digital surface points from the sampled spline points; and determining associated digital surface points corresponding to each sampled digital surface point.

Abstract: Sensor data fusion systems that provide noise reduction and fault protection. The sensor data fusion system fuses data acquired by respective accelerometers having different attributes. For example, one accelerometer has low noise and high bias, while another accelerometer has high noise and low bias when measuring specific force. The high-noise, low-bias accelerometer may be a gravimeter. Gravimeters and traditional accelerometers measure the same physical variable, i.e., specific force. By combining an expensive gravimeter and low-cost accelerometers, a synthetic sensor having both low noise and low bias may be achieved. Such synthetic sensors may be utilized in a gravity anomaly-referenced navigation system to achieve improved navigation performance.