CT imaging parameters for precision models using additive manufacturing

Abstract

Additive manufacturing (AM), generally known as 3D Printing, is one of the manufacturing methods to develop medical models. The AM physical medical models are manufactured by virtual Computer-Aided Design (CAD) models. These CAD models are generated using medical scan data such as, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), etc. In the process of CT data acquisition and transformation from CT to CAD data, dimensional and volumetric errors occur. In this work, the influence of several CT image reconstruction parameters on the 3D CAD model was evaluated experimentally. The dry mandible has been considered as a phantom from construction of a 3D CAD model. The linear dimensional and volumetric errors in the CT image reconstruction were compared from the dry mandible to the 3D CAD model of the CT images. Further, the CT image reconstruction parameters are optimized by Taguchi and Gray relational analysis methods. The optimized parameter of a 3D CAD model was used to develop STereo Lithography (STL) file and Fused Deposition Modeling (FDM) model by AM process. The scaling factor of each axis is determined by considering the ratio of STL to FDM model linear dimensions. Finally, the scaled STL model was manufactured by FDM technique and investigated that the dimensional error of the FDM model was minimized.