Automatic extraction of interdental gingiva regions for accurate statistical shape from shading-based reconstruction of human jaw
The three-dimensional (3D) reconstruction of visible part of the human jaw is becoming required for many of diagnostics and treatment procedures. In our previous work [1], we proposed a novel approach for 3D reconstruction of human jaw using Statistical Shape from Shading (SSFS). The input of this approach has to be a single optical image of the jaw augmented manually with several requirements; anatomical landmark points, jaw status and the number of teeth per jaw. In this paper, we boost our SSFS framework by proposing a novel approach to automatically extract these prior information. This two-step framework consists of: Interdental gingiva's regions extraction for each individual tooth and detects the centerline across the jaw span. These two steps help us to extract the anatomical landmark points and detect the status of the jaw. Experimental results highlight the accuracy of the extracted prior information and how this information boosts recovering 3D models of the human jaw.