Investigate on Skull Defect Reconstruction Technologies

Abstract

Skull reconstruction is a promising and significant research topic in patient treatment. The process involves several steps including identifying the location of skull defects, designing grafts, manufacturing grafts, and surgery. In the step of identifying the location of skull defects, we can easily determine the position thanks to images of the defective skull captured by advanced imaging technologies such as CT and MRI. During the manufacturing step, 3D printing technology makes it easy to manufacture the grafts. Skull graft surgery is the final step. The accuracy in designing the graft piece is crucial for the success of the surgical procedure. The design step of the graft is the most important, with many challenges. Previously, design was done using commercial CAD software or some online platforms. It involves a series of steps such as segmentation, noise filtering, and refinement to achieve the desired shape of the graft. The complex steps increase processing time and depend on the processing technique of the technician. This causes difficulties and prolongs the treatment process for the patient. Currently, the method of using deep learning to reconstruct graft pieces is a new approach thanks to increasingly advanced AI technology. The advantages and disadvantages of these methods will be presented and discussed in this study.

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