Reduction of artifacts in dental cone beam CT images to improve the three dimensional image reconstruction
Open Access
- 1 January 2012
- journal article
- Published by Scientific Research Publishing, Inc. in Journal of Biomedical Science and Engineering
- Vol. 05 (08), 409-415
- https://doi.org/10.4236/jbise.2012.58052
Abstract
Cone-beam CT (CBCT) scanners are based on volumetric tomography, using a 2D extended digital array providing an area detector [1,2]. Compared to traditional CT, CBCT has many advantages, such as less X-ray beam limitation, and rapid scan time, etc. However, in CBCT images the x-ray beam has lower mean kilovolt (peak) energy, so the metal artifact is more pronounced on. The position of the shadowed region in other views can be tracked by projecting the 3D coordinates of the object. Automatic image segmentation was used to replace the pixels inside the metal object with the boundary pixels. The modified projection data, using synthetically Radon Transformation, were then used to reconstruct a new back projected CBCT image. In this paper, we present a method, based on the morphological, area and pixel operators, which we applied on the Radon transformed image, to reduce the metal artifacts in CBCT, then we built the Radon back project images using the radon invers transformation. The artifacts effects on the 3d-reconstruction is that, the soft tissues appears as bones or teeth. For the preprocessing of the CBCT images, two methods are used to recognize the noisy black areas that the first depends on thresholding and closing algorithm, and the second depends on tracing boundaries after using thresholding algorithm too. The intensity of these areas is the lowest in the image than other tissues, so we profit this property to detect the edges of these areas. These two methods are applied on phantom and patient image data. It deals with reconstructed CBCT dicom images and can effectively reduce such metal artifacts. Due to the data of the constructed images are corrupted by these metal artifacts, qualitative and quantitative analysis of CBCT images is very essentialKeywords
This publication has 13 references indexed in Scilit:
- Conebeam CT of the Head and Neck, Part 1: Physical PrinciplesAmerican Journal of Neuroradiology, 2009
- Fast accurate stereoradiographic 3D-reconstruction of the spine using a combined geometric and statistic modelClinical Biomechanics, 2004
- A Biplanar Reconstruction Method Based on 2D and 3D Contours: Application to the Distal FemurComputer Methods in Biomechanics and Biomedical Engineering, 2003
- 3D reconstruction of the brain from magnetic resonance images using a connectivity algorithmMagnetic Resonance Imaging, 1987
- Image space shading of 3-dimensional objectsComputer Vision, Graphics, and Image Processing, 1985
- Color 3-D Imaging of Normal and Pathologic Intracranial StructuresIEEE Computer Graphics and Applications, 1984
- Three-Dimensional Reconstruction of Craniofacial Deformity Using Computed TomographyNeurosurgery, 1983
- Conversion of complex contour line definitions into polygonal element mosaicsACM SIGGRAPH Computer Graphics, 1978
- Optimal surface reconstruction from planar contoursCommunications of the ACM, 1977
- Approximating Complex Surfaces by Triangulation of Contour LinesIBM Journal of Research and Development, 1975