Skull part relationships and shape prediction toward the missing part completion
by Tan-Nhu Nguyen; Ngoc-Bich Le; Xuan-Hien Quach-Nguyen; Thi-Hiep Nguyen; Van-Toi Vo; Tien-Tuan Dao
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 46, No. 4, 2024

Abstract: Accurate cranial reconstruction needs clear relation among skull parts due to the asymmetry of the skull structures. Consequently, this study investigated the relation among skull parts for enhancing the skull missing part prediction. The relationship was trained from three-dimensional skull shapes reconstructed from 329 head-and-neck computed tomography images. We automatically defined the skull parts throughout all skull shapes. The skull parts were parameterised using the principal component analysis (PCA). Skull part relations were trained through their PCA-based shape parameters. The output skull parts could be predicted from the input skull parts with the trained shape relation with good and acceptable accuracy in cranial reconstruction. The best and worst mean errors were 1.32 mm and 2.54 mm when the number of missing skull parts was one and ten, respectively. The investigated procedure was employed in a computer-aided system for automatically predicting and printing skull missing parts directly in 3D spaces.

Online publication date: Thu, 12-Dec-2024

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