###### Abstract
[24; 25], which comprises medical models for planning, medical aids, tools for medical devices, inert implants, and bio-manufacturing. [PERSON] et al. [26] have extended the classification of custom-made inert implants to intelligent implants containing patient-specific digital data and drug delivery systems. The advent of preoperative virtual planning, based on medical imaging, segmentation, implant modeling, and manufacturing [27] in particular with AM techniques, has enabled excellent functional and aesthetic reconstruction of different craniomaxillofacial surgical procedures including the reduction of intraoperative time [28; 29; 30; 31; 32; 33]. The craniomaxillofacial, in particular the mandibular, deformities can be caused by tumor, injuries, and/or infections [34]. The reconstruction of mandibles followed by an ablative tumor surgery poses a challenge for practitioners [31]. This is due to the nature of complex 3D patient-specific geometry that is difficult to replicate. Any signs of an aberration in its structural alignment may lead to functional disturbance due to the malocclusion or temporomandibular disorders [33]. Further, difficulties may arise due to extensive bone resection, temporomandibular joint involvement, or severely distorted bony contour [33]. Evidently, the development of medical imaging, in particular computed tomography (CT) techniques, has changed the dynamics of the medical industry because it has enabled data capture from the interior and exterior of the patient-specific anatomy. This captured data is volumetric in nature comprising 3D block of smaller cuboid structures called voxels (volume element). Each voxel represents a relative X-ray attenuation [35] that is characterized by grey scale values in Hounsfield unit (HU). More specifically, the Hounsfield units represent material X-ray attenuation value relative to water. In principle, this relationship enables a calibration of CT images by means of the grey scale range. The slice-by-slice captured voxels are interpreted by stacking the slices to obtain multiple 2D representations [35]. The CT images are generally stored in 16 bits according to the international standard of digital imaging and communications in medicine (DICOM) format. CT imaging can essentially be performed using either a fan-beam multi-slice CT (MSTC) or a cone-beam CT (CBCT) system depending on the geometry of the X-ray acquisition [35]. Further, a dual-energy CT (DECT) system provides more possibilities for the clinical applications by acquiring CT images using two different X-ray spectra [36]. Though a MST system may provide a higher low-contrast resolution, a reduced image noise [37], and a rapid scan time [35], a CBCT system is increasingly used in the maxillofacial surgeries owing to an acceptable image quality [38], a similar scanning time [35; 37], a lower cost, and a reduced radiation dose [35; 37; 38; 39]. Regarding the quality assurance (QA) of the CT systems, QA programs for the MST system are well-established. However, the QA programs for the CBCT system are still evolving and present only a few established sources, i.e., programs for high-end and large-volume CBCTsystems [40], the QA program proposed by the SEDENTEXCT Project [41], and the EFOMP CBCT QA Protocol [42]. The standardized QA Phantoms including the European project-based [41], commercial [43], and low-cost alternatives [44] enable the assessment of accuracy and quality of the CT systems [40]. The composition of a Phantom varies according to the application and involves several properties, i.e., radiation type, energy range, linear attenuation coefficient, and density, which mimic water or body tissues by means of attenuating photons [45]. Though conventional 2D representations of medical images benefit from the localized analysis of different anatomical structures, a reconstruction of medical images to a 3D model enables enhanced visualization of craniomaxillofacial structures, deformities, and implant sites [37; 46; 47].