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Eldib, Mohamed Elsayed,Hegazy, Mohamed A.A.,Cho, Myung Hye,Cho, Min Hyoung,Lee, Soo Yeol Elsevier 2018 Computers in biology and medicine Vol.103 No.-
<P><B>Abstract</B></P> <P>High-resolution imaging is essential in three-dimensional (3D) CT image-based digital dentistry. A small amount of head motion during a CT scan can degrade the spatial resolution of the images to the extent where the efficacy of 3D image-based digital dentistry is greatly compromised. We introduce a retrospective motion artifact reduction (MAR) method for dental CTs that eliminates the necessity for any external motion tracking devices. Assuming that rigid-body motions are dominant in a dental scan of a human head, we extracted motion information from the projection data. By taking the cross-correlation between two successive projection data for every projection view, we determined the displacement of the projection data at each view. We experimentally found that any motion of the imaging object during the scan resulted in displacement of the projection data proportional to the motion amplitude. We decomposed the displacement into two components, one caused by translational motion and the other caused by rotational motion. The displacement components were used to correct the projection data before CT image reconstruction. We experimentally verified the MAR method using the projection data of a few phantoms acquired through a clinical dental CT machine. When the MAR performance was evaluated by the structural similarity index (SSIM) and the normalized absolute error (NAE) in reference to the motion-less images, the SSIM improved to 99% while the NAE was reduced by 80–90%.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We introduce a retrospective motion artifact reduction (MAR) method for a dental CT. </LI> <LI> A subpixel image registration technique is used to estimate the motion-induced displacements. </LI> <LI> The proposed method can estimate all the motion components including translation and rotation. </LI> <LI> Actuator-controlled and manual motions have been applied on phantoms using a clinical dental CT. </LI> <LI> The experimental results demonstrate the high performance of the proposed method. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
A head motion estimation algorithm for motion artifact correction in dental CT imaging
Hernandez, Daniel,Eldib, Mohamed Elsayed,Hegazy, Mohamed A A,Cho, Myung Hye,Cho, Min Hyoung,Lee, Soo Yeol Institute of Physics in association with the Ameri 2018 Physics in medicine & biology Vol.63 No.6
<P>A small head motion of the patient can compromise the image quality in a dental CT, in which a slow cone-beam scan is adopted. We introduce a retrospective head motion estimation method by which we can estimate the motion waveform from the projection images without employing any external motion monitoring devices. We compute the cross-correlation between every two successive projection images, which results in a sinusoid-like displacement curve over the projection view when there is no patient motion. However, the displacement curve deviates from the sinusoid-like form when patient motion occurs. We develop a method to estimate the motion waveform with a single parameter derived from the displacement curve with aid of image entropy minimization. To verify the motion estimation method, we use a lab-built micro-CT that can emulate major head motions during dental CT scans, such as tilting and nodding, in a controlled way. We find that the estimated motion waveform conforms well to the actual motion waveform. To further verify the motion estimation method, we correct the motion artifacts with the estimated motion waveform. After motion artifact correction, the corrected images look almost identical to the reference images, with structural similarity index values greater than 0.81 in the phantom and rat imaging studies.</P>
Dual‐energy‐based metal segmentation for metal artifact reduction in dental computed tomography
Hegazy, Mohamed A. A.,Eldib, Mohamed Elsayed,Hernandez, Daniel,Cho, Myung Hye,Cho, Min Hyoung,Lee, Soo Yeol Published for the American Association of Physicis 2018 Medical physics Vol.45 No.2
<P>Conclusions: The proposed dual-energy-based method has shown better performance in metal segmentation leading to better MAR performance in dental imaging. We expect the proposed metal segmentation method can be used to improve the MAR performance of existing MAR techniques that have metal segmentation steps in their correction procedures. (C) 2017 American Association of Physicists in Medicine</P>