Abstract
The use of Cone-Beam Computed Tomography (CBCT) scanner has become powerful tools for medical imaging techniques. This will allow medical surgeons and radiologist assistants to diagnose patients before any treatment can be taken place. However, the CBCT concepts require high demand for computer resources to reconstruct three-dimensional (3D) model from two-dimensional (2D) images. Based on this problem, Open Source Cone-Beam Reconstructor (OSCaR) was used to train medical and biomedical engineering students in understanding the concepts of computed tomography scanner. This software requires only a small capacity of computer resources, thus allowing students to practise using their own computer. With a small number of projections, the authors evaluated the performance of OSCaR to reconstruct 36 numbers of 2D x-ray images. By using the cone-beam x-ray tube, 36 images of lemon and chicken bone were captured and saved into Digital Imaging and Communication in Medicine (DICOM) files. The DICOM files were then imported to the OSCaR software for the reconstruction process. Based on the results, this study successfully reconstructed 3D images of lemon and chicken bone. In conclusion, higher number of projections would produce better results in terms of accuracy and high resolution. However, the use of 36 numbers of 2D images is adequate for students to understand the concepts of computed tomography scanner.
Highlights
The basic concepts of Cone-Beam Computed Tomography (CBCT) scanner is allocated in capturing images of the maxillofacial, from 2D images to a 3D model approach based on the concepts of data acquisition and image reconstruction [1]
The conebeam reconstruction can be referred as an image reconstruction from 2D projections data into 3D volume where the basic fundamental of capture through 2D x-ray area detector and cone-beam geometry
FDK conebeam reconstruction is an approximation of the exact reconstruction problem developed for technical purposes [4]
Summary
The basic concepts of Cone-Beam Computed Tomography (CBCT) scanner is allocated in capturing images of the maxillofacial, from 2D images to a 3D model approach based on the concepts of data acquisition and image reconstruction [1]. The conebeam reconstruction can be referred as an image reconstruction from 2D projections data into 3D volume where the basic fundamental of capture through 2D x-ray area detector and cone-beam geometry. The first and most popular approximate reconstruction scheme for cone-beam projections acquired along a circular trajectory is the algorithm from Feldkamp and colleagues [3]. The algorithm is namely as the Feldkamp, Davis, and Kress (FDK) method which is a derivative-free method [4]. FDK conebeam reconstruction is an approximation of the exact reconstruction problem developed for technical purposes [4]
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