Abstract: Disclosed techniques include radiograph analysis based on Mach band effects. A dental radiographic image is obtained. A high contrast structure on the image is detected. The high contrast structure comprises a radiopaque structure. The structure is analyzed to identify a dental restoration. Contrast is evaluated for the presence of Mach band effects from the dental restoration. A boundary for the dental restoration is determined based on the analyzing and the evaluating. The image is colorized to display the dental restoration based on the boundary that was determined wherein the color for the dental restoration is represented as a darker color than originally on the image.

Abstract: Disclosed are implementations that include a method for dental data analysis including obtaining dental data for an individual, with the dental data being input radiographic image data of at least one dental object, and treatment data representative of one or more treatment procedures associated with the dental object, analyzing, by machine learning models, the input radiographic image data to identify one or more dental features associated with the dental object, and deriving, based on the treatment data and the identified one or more dental features, one or more integrity scores for the image data and the treatment data, with the one or more integrity scores being representative of potential integrity problems associated with the input radiographic image data and the treatment data. Deriving the integrity scores includes deriving a provider score representative of a potential integrity problem associated with a dental-care provider submitting the treatment data.

Abstract: Disclosed are implementations that include a clinical data analysis method including obtaining dental data that includes input radiographic image data for at least one dental object, and identifying, by machine learning models, a first dental feature in the input radiographic image data for the at least one dental object, and at least one other feature in the dental object comprising at least partly a healthy dental structure. The method additionally includes computing at least one dimensioned property representative of physical dimensions of the first dental feature and the at least one other feature, deriving, based on the computed at least one dimensioned property, a ratio indicative of an extent of a dental clinical condition associated with the identified first dental feature, and determining a treatment plan based on a comparison of the at least one dimensioned property ratio to a respective threshold value.

Abstract: A computer-implemented method and system provide point of care processing of an insurance claim relating to oral care delivered to a subject patient during a visit of the patient to a dental clinic. The method includes processing, by a computer system, of dental image data and patient data, using a set of machine learning models, to extract output representative of diagnostic data characterizing the dental image data; determining, by a decision support system a claim decision based on the diagnostic data; and communicating the claim decision in real time to an endpoint located in the dental clinic.

Abstract: Disclosed techniques include radiograph analysis based on Mach band effects. A dental radiographic image is obtained. A high contrast structure on the image is detected. The high contrast structure comprises a radiopaque structure. The structure is analyzed to identify a dental restoration. Contrast is evaluated for the presence of Mach band effects from the dental restoration. A boundary for the dental restoration is determined based on the analyzing and the evaluating. The image is colorized to display the dental restoration based on the boundary that was determined wherein the color for the dental restoration is represented as a darker color than originally on the image.

Abstract: Disclosed are implementations that include a method for dental data analysis including obtaining dental data for an individual, with the dental data being input radiographic image data of at least one dental object, and treatment data representative of one or more treatment procedures associated with the dental object, analyzing, by machine learning models, the input radiographic image data to identify one or more dental features associated with the dental object, and deriving, based on the treatment data and the identified one or more dental features, one or more integrity scores for the image data and the treatment data, with the one or more integrity scores being representative of potential integrity problems associated with the input radiographic image data and the treatment data. Deriving the integrity scores includes deriving a provider score representative of a potential integrity problem associated with a dental-care provider submitting the treatment data.

Abstract: Disclosed are implementations that include a clinical data analysis method including obtaining dental data that includes input radiographic image data for at least one dental object, and identifying, by machine learning models, a first dental feature in the input radiographic image data for the at least one dental object, and at least one other feature in the dental object comprising at least partly a healthy dental structure. The method additionally includes computing at least one dimensioned property representative of physical dimensions of the first dental feature and the at least one other feature, deriving, based on the computed at least one dimensioned property, a ratio indicative of an extent of a dental clinical condition associated with the identified first dental feature, and determining a treatment plan based on a comparison of the at least one dimensioned property ratio to a respective threshold value.

Abstract: A method and system for receiving a dental radiographic image that includes an oral structure, and in an image processor, selecting a segmenter and an object detector, predicting masks and points of the oral structure using the segmenter and the object detector to become part of image metadata. The dental radiographic image and image metadata are further provided to a measurement processor for selecting at least one measurement method of a set of measurement methods according to the dental radiographic image and the image metadata, calculating a sensor pixel to mm (millimeter) ratio using the measurement method, and calculating a calibrated measurement of the oral structure.

Abstract: A method and system for receiving a dental radiographic image that includes an oral structure, and in an image processor, selecting a segmenter and an object detector, predicting masks and points of the oral structure using the segmenter and the object detector to become part of image metadata. The dental radiographic image and image metadata are further provided to a measurement processor for selecting at least one measurement method of a set of measurement methods according to the dental radiographic image and the image metadata, calculating a sensor pixel to mm (millimeter) ratio using the measurement method, and calculating a calibrated measurement of the oral structure.

Abstract: A reconfigurable antenna system includes an antenna array; a set of metamaterial panels configured to surround the antenna array; a control unit, coupled to each of the metamaterial panels, for selectively addressing each of the metamaterial panels to control separately at least one property of each of the metamaterial panels; and a receiver coupled to the antenna array and to the control unit. The control unit is configured to monitor signal reception by the antenna array via the receiver and to establish a set of configurations of the metamaterial panels to produce a pattern of reception according to a set of prespecified criteria that include a set of azimuthal and elevational ranges characterizing the configurations. Optionally, the system further includes a transmitter coupled to the antenna array and to the control unit.

Abstract: A reconfigurable antenna system includes an antenna array; a set of metamaterial panels configured to surround the antenna array; a control unit, coupled to each of the metamaterial panels, for selectively addressing each of the metamaterial panels to control separately at least one property of each of the metamaterial panels; and a receiver coupled to the antenna array and to the control unit. The control unit is configured to monitor signal reception by the antenna array via the receiver and to establish a set of configurations of the metamaterial panels to produce a pattern of reception according to a set of prespecified criteria that include a set of azimuthal and elevational ranges characterizing the configurations. Optionally, the system further includes a transmitter coupled to the antenna array and to the control unit.

Abstract: The systems and methods described herein are directed towards a microgrid having modular power management units to control and regulate power to maintain a stable energy environment and provide peer-to-peer electricity sharing within the microgrid. The microgrid includes a power source to generate power for the microgrid, a source power management unit coupled to the power source to receive the power, one or more load power management units coupled to the source power management unit to receive a portion of the power and a bi-directional communication system to couple the source power management unit to the one or more load power management units to control and allocate the power from the source power management unit to the one or more load power management units.