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A beam-hardening effect is a common problem affecting the quantitative aspects of X-ray computed tomography (CT). We have developed two statistical reconstruction algorithms for poly-energetic X-ray CT that can effectively reduce the beam-hardening effect. Phantom tests were used to evaluate our approach in comparison with traditional correction methods. Unlike previous methods, our algorithm utilizes multiple energy-corresponding blank scans to estimate the attenuation map for a particular energy spectrum. Therefore, our algorithm is an energy-selective reconstruction. In addition to benefits over other statistical algorithms for poly-energetic reconstruction, our algorithm has the advantage of not requiring prior knowledge of the object material, the energy spectrum of the source and the energy sensitivity of the detector. The results showed an improvement in coefficient of variation, uniformity and signal-to-noise ratio; overall, this novel approach produces a better beam-hardening correction.

Micro-X-ray computed tomography (micro-CT) has several characters such as non-invasive, high spatial resolution, high signal-to-noise ratio, providing three-dimensional volume information. Because micro-CT was utilized in many kinds of research field such as preclinical biomedical study, designing a performance phantom and developing analytic methods to objectively evaluate the performance of micro-CT are very important. In this study, the performance phantom and the analytic methods were developed for performance evaluation of micro-CT. The performance parameters extracted from different CT images including noise, linearity, spatial resolution, and hardware alignment were defined in the American Association of Physicists in Medicine (AAPM) Report No. 1 and the American Society for Testing and Materials (ASTM) E1695-95. Standard deviation, Pearson's correlation coefficient, edge response function, and visualization method were utilized to evaluate noise, linearity, spatial resolution, and hardware alignment, respectively. A digital uniform disk image was utilized to evaluate the accuracy of spatial resolution evaluation method. The physical phantom study was performed to evaluate a home-made micro-CT and a commercial micro-CT (Skyscan 1076). According to these results, the performance phantom and the analytic methods developed in this study have demonstrated their capability to evaluate performance of any micro-CT.

Purpose: Cone-beam micro computed tomography CT (micro-CT) can offer comprehensive 3D information and high-resolution images. This technology can be used with other imaging modalities in the preclinical application of molecular imaging research. Image reconstruction algorithm affects final image spatial resolution, which is the primary topic of this study. We use two types of reconstruction methods, which are analytical (tent-FDK) and statistical iterative (convex algorithm) algorithms, to reconstruct the micro-CT images for evaluation. Materials and Methods: In this study, projection data of the Defrise phantom and HA (Hydroxy-Apatite) phantom were obtained using an in-house designed micro-CT imaging system and images were reconstructed with the tent-FDK and convex algorithms. We develop a new way to calculate the system matrix of our micro-CT. Human tooth sample and mouse bone sample data were reconstructed with the analytic and iterative algorithms. Results: The Defrise phantom results show coronal view of the images reconstructed by the tent-FDK and convex algorithms. From the profile of the results, image reconstructed by the convex algorithm has higher pixel value in the high-density layer. Comparison of the results of human tooth sample and mouse bone sample reconstructed by the two kinds of algorithms, the image reconstructed by the convex algorithm has fewer artifacts and more correct pixel value representing for the attenuation coefficients. Conclusion: Tent-FDK algorithm is a kind of useful analytic method to reconstruct cone-beam CT data. We also develop the convex iterative method to reconstruct images for low dose X-ray cone-beam CT, which performs better than the analytical one in general.

The term input function usually refers to the tracer plasma time activity curve (pTAC), which is necessary for quantitative positron emission tomography (PET) studies. The purpose of this study was to acquire the pTAC from the independent component analysis (ICA) estimated whole blood time activity curve (wTAC) using our proposed method: FDG blood-cell-two-compartment model (BCM). We also compared published models, which are linear haematocrit (HCT) correction, nonlinear HCT correction, and two-exponential correction. According to the results, the normalized root mean square error (NRMSE) and error of area under curve (EAUC) of BCM estimated pTAC were the smallest. Compartmental and graphic analyses were used to estimate metabolic rate of FDG (MR FDG ). The percentage error of MR FDG (PE MRFDG ) estimated from BCM corrected pTAC was also the smallest. The BCM is a better choice to transfer wTAC to pTAC for quantification.

A beam-hardening effect is a common problem affecting the quantitative ability of X-ray computed tomography. We develop a statistical reconstruction for a poly-energetic model, which can effectively reduce beam-hardening effects. A phantom test is used to evaluate our approach in comparison with traditional correction methods. Unlike previous methods, our algorithm utilizes multiple energy-corresponding blank scans to estimate attenuation map for a particular energy spectrum. Therefore, our algorithm has an energy-selective reconstruction. In addition to the benefits of other iterative reconstructions, our algorithm has the advantage in no requirement for prior knowledge about object material, energy spectrum of source and energy sensitivity of the detector. The results showed an improvement in the coefficient of variation, uniformity and signal-to-noise ratio demonstrating better beam hardening correction in our approach.

The term input function usually refers to the tracer plasma time activity curve (pTAC), which is necessary for quantitative positron emission tomography (PET) studies. The purpose of this study was to acquire the pTAC by independent component analysis (ICA) estimation from the whole blood time activity curve (wTAC) using a novel method, namely the FDG blood-cell-two-compartment model (BCM). This approach was compared to a number of published models, including linear haematocrit (HCT) correction, non-linear HCT correction and two-exponential correction. The results of this study show that the normalized root mean square error (NRMSE) and the error of the area under curve (EAUC) for the BCM estimate of the pTAC were the smallest. Compartmental and graphic analyses were used to estimate the metabolic rate of the FDG (MR"F"D"G). The percentage error for the MR"F"D"G (PE"M"R"F"D"G) was estimated from the BCM corrected pTAC and this was also the smallest. It is concluded that the BCM is a better choice when transferring wTAC into pTAC for quantification.

Quantitative computed tomography provides the most accurate form of bone mineral density measurement. It is very useful in several applications when used with micro computed tomography (microCT). The objective of this study is to evaluate the quantitative capability of iterative and analytic reconstruction with and without energy-based beam hardening calibration using a home-made microCT. Due to the fact that the source of X-rays in the microCT is poly-energetic and the linear attenuation coefficient varies with the energy of the X-ray photons, a specific correction is presented in this study that resolves the poly-energetic effect. Then, a 3D distribution of the linear attenuation coefficient is reconstructed from the ordered subsets using the maximum likelihood and T-FDK algorithms. These algorithms were both developed for cone-beam microCT. The images reconstructed by the two algorithms with/without correction are presented. A region of interest analysis is used to evaluate the results from two algorithms and their advantages and disadvantages are discussed. The quantitative capability is better when the image is reconstructed using the iterative method along with a beam hardening correction.