Abstract: Technologies are disclosed for detection and display of an indication of a gingivitis condition and/or a periodontal pocket assessment of a subject's oral cavity via a digital representation of the oral cavity. Using scan data of the oral cavity, one or more teeth in the oral cavity may be indicated. A first assessment location proximate to a first tooth of the one or more teeth may be indicated. A first image may be generated that may include the first assessment location and one or more first data channels. The one or more first data channels may comprise color data and topological information corresponding to the first assessment location. Using one or more machine-learning algorithms, a modified gingival index (MGI) value and/or a periodontal pocket depth assessment may be determined and displayed for the first assessment location based on the first image and the one or more first data channels.

Abstract: According to an embodiment, a method for generating a digital three-dimensional model representing development in dental condition for a tooth is disclosed. The method includes obtaining, at different timepoints, a first digital 3D model of a patient's set of teeth including first texture data and a second digital 3D model of the patient's set of teeth including second texture data. The first digital 3D model including the first texture data and second digital 3D model including the second texture data are placed in a common texture space by uniformizing texture. Lastly, the digital three-dimensional model representing development in dental condition is generated based on a comparison of the first texture data and the second texture data of corresponding regions in the first digital 3D model and the second digital 3D model placed in the common texture space.