Automatic dental boundary feature identification method

Abstract

The invention relates to a dental jaw boundary feature automatic identification method. The method comprises the steps of performing three-dimensional scanning to obtain dental jaw three-dimensional data; defining a parabola in the center of a dental jaw region needing to define boundary characteristics; establishing a plurality of sectioning surfaces along a plurality of points on the parabola, wherein the sectioning surfaces are vertical to the parabola; calculating curvatures of a plurality of points on an intersecting line of the section cutting surface and the dental jaw region, and defining a starting point and an ending point of the curvatures from positive to negative; extending the tangent lines of the curves on the two sides of the starting point and the terminal point to intersect to obtain an intersection point A; projecting the point A onto the intersecting line of the section cutting plane and the dental jaw region to obtain a boundary feature point A' on the section cutting plane; and connecting the points A' on the plurality of section cutting surfaces to obtain the three-dimensional characteristic line of the dental jaw boundary. The method can digitalize the logicobserved by oral medical experts, is applied to automatic identification and definition of dental boundary feature points and lines, can greatly improve the intelligence, automation degree and efficiency of software, and can be directly applied to development of related artificial intelligence algorithms.

Description

technical field [0001] The invention relates to an artificial intelligence design method, in particular to an automatic recognition method for dental and jaw boundary features. Background technique [0002] In the digital design process of the existing oral diagnosis and treatment plan and diagnosis and treatment device, all kinds of dental and jaw boundary features are recognized as the premise, such as the junction line between the tooth and the gum, the refraction line of the mucosa, the edge line of the tooth preparation, the two teeth boundary line between etc. However, it is very difficult for grass-roots dental staff to obtain the best dental and jaw boundary characteristics, so as to achieve the optimal oral diagnosis and treatment plan, and it is easy to have defects in oral diagnosis and treatment, which cannot be made up. [0003] Currently, the machine learning and data mining algorithms used in dental and jaw feature recognition mostly use microscopic features ...

AI Technical Summary

Problems solved by technology

However, it is very difficult for grass-roots dental staff to obtain the best dental and jaw boundary characteristics, so as to achieve the optimal oral diagnosis and treatment plan, and it is prone to defects in oral diagnosis and treatment, which cannot be remedied.

[0003] The current machine learning and data mining algorithms used in dental feature recognition mostly use microscopic features of two-dimensional pixels or triangular faces, which is inefficient and insufficient in accuracy.

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