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.

Abstract: Methods and apparatus to reduce communications for position, navigation and timing (PNT) determinations are disclosed. A disclosed example apparatus to enable PNT determination for a mobile station includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify features of signals of opportunity (SOOP) measured at a reference station, generate a model based on the identified features of the SOOP in conjunction with a position and a timing of the reference station, and provide at least one of the model or parameters associated with the model to the mobile station for the PNT determination.

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: 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.