The Added Value of 3D Imaging and 3D Printing in Head and Neck Surgeries

3D Imaging In The Medical Field

Medical Imaging is as a group of methods that focus on the noninvasive generation of images derived by the interaction of energy with biological tissue. Some of the most prevalent medical imaging techniques are computed tomography (C.T.), magnetic resonance imaging (MRI), and ultrasound imaging (U.I.). C.T. is a computerized x-ray imaging procedure in which a narrow beam of x-rays is aimed at a patient and quickly rotated around the body, producing signals that are processed computationally, generating cross-sectional image slices of the body, which are called tomographic images. A 3D image of the patient can be created by stacking the successive 2D slices. MRI is a technique that is based on a magnetic field and computer-generated radio waves to produce detailed images of the organs and tissues of the human body. A 3D M.R. image is created by joining together the 2D M.R. slices. U.I. is based on the application of sound waves instead of radiation, and 3D U.S. images can be generated with the volume rendering of ultrasound data (Junn et al., 2020).

Image reconstruction refers to the process of generating axial images from non-invasively acquired projection data. A set of 3D voxels represents objects, and every projection group is a 2D layout, also called a projection image. Image reconstruction algorithms can be outlined as simple back projection, filtered back projection and iterative reconstruction algorithms. The goal of these algorithms is to solve the inverse Radon transform to estimate the image to be reconstructed using the projection data. These methods are mainly implemented in 2D but can be extended in three dimensions. Ideally, a large number of projection rads and projection angles has to be used for the production of a high-resolution tomographic image.

The main 3D visualization techniques are surface rendering and volume rendering. Surface rendering involves the polygonalisation of the regions of interest, using a form of iso contours. In contrast, volume rendering consists of the formation of volumes based on the RGBA color values of the data. These procedures can be performed simultaneously using reconstruction software tools (Moon et al., 2016).