• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.46-51
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• 2008

We describe a backprojection filtering method for limited angle tomography. In order to reduce blur artifacts originated from the out-of-planes and control high-frequency noise, we employed two band-limited window functions, and which were realized by Hann filters in this study. Based on the experimentally measured data, the performance of the developed method is demonstrated by comparing with the conventional shift-and-add and filtered backprojection methods. Application of the developed method to the dental imaging has a potential to be used for the preoperative evaluation of the jaw for dental implants with much reduced patient dose instead of the conventional dental computed tomography.

• Progress in Medical Physics
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• v.21 no.3
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• pp.281-290
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• 2010

Cone-beam digital tomosynthesis (CBDT) has greatly been paid attention in the image-guided radiation therapy because of its attractive advantages such as low patient dose and less motion artifact. Image quality of tomograms is, however, dependent on the imaging conditions such as the scan angle (${\beta}_{scan}$) and the number of projection views. In this paper, we describe the principle of CBDT based on filtered-backprojection technique and investigate the optimization of imaging conditions. As a system performance, we have defined the figure-of-merit with a combination of signal difference-to-noise ratio, artifact spread function and floating-point operations which determine the computational load of image reconstruction procedures. From the measurements of disc phantom, which mimics an impulse signal and thus their analyses, it is concluded that the image quality of tomograms obtained from CBDT is improved as the scan angle is wider than 60 degrees with a larger step scan angle (${\Delta}{\beta}$). As a rule of thumb, the system performance is dependent on $\sqrt{{\Delta}{\beta}}{\times}{\beta}^{2.5}_{scan}$. If the exact weighting factors could be assigned to each image-quality metric, we would find the better quantitative imaging conditions.