Three-dimensional reconstruction of cone beam computed tomography images using oscar-analysis on 36 projections

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.