Overjet, Inc.

Samet Taspinar

Wardah Inam

Deepak Ramaswamy

Alexander Albert Joseph Jelicich

Robert Faiella

Shaju Puthussery

Jack C Kwok

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.

Automatic reduction of the appearance of Mach band effect on radiographs

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.

Systems and methods for integrity analysis of clinical data

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.

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Brooklyn, NY, United States of America

Samet Taspinar