With the appearance of the field-emission cold cathode x-ray source, the fast response and small in size innovate the traditional imaging system. Although the field-emission x-ray source array generates multiple novel imaging modalities, it still faces a long stand-off distance between source and object. To realize a portable, smart, extremely low dose imaging modality, researchers proposed a concept to design a two-dimensional array field-emission source, namely the flat-panel source. In this paper, a real imaging system based on the ZnO field-emission flat-panel source is designed. Currently, the real flat-panel source faces an extremely low dose and non-addressable situation. Hence, the measurement based on the flat-panel source is overlapped and without an application potential. We first try to realize the imaging ability of the flat-panel source by designing a rebinning algorithm. With the analysis on the overlapped measurement, a high-order prior is introduced into the rebinning algorithm to improve the performance. Simulation and real data experiments verified our proposed method. Compared to the no high-order prior, the proposed algorithm can recover a more distinct measurement.
The X-ray source using ZnO nanowires as the cold cathode is first densely integrate a large number of X-ray sources into flat panel devices. Compared with traditional ray sources, X-ray sources device based on ZnO nanowires have small size, instantaneous response, and can be electronically controlled. We propose a new conformal transmission imaging system that uses this flat-panel ray source to irradiate objects with multiple points to complete extremely low-dose projection. In order to get the final image, it is necessary to process the original projection with an image restoration method to remove the projection aliasing caused by multiple point sources. Due to the addition of iteration in the image restoration process, the error caused by the geometric parameters will gradually become larger as the iteration progresses, resulting in distortion of the final image. Therefore, geometric correction of the imaging system is required. The new imaging system has a unique geometric relationship. Based on this geometric relationship, this paper proposes a geometric correction method applied to the new imaging scheme. In this method, the angle parameters in the new imaging system are estimated using a single point volume model. It only needs one projection of the phantom, and it can derive the analytical formula about the three angle errors, which can avoid falling into a local minimum. In this paper, we give the simulation results of the calibration method, which proves the validity and accuracy of the method.
X-ray spectrum plays an essential role in CT applications. Since it is difficult to measure x-ray spectrum directly in practice, x-ray spectrum is always indirectly obtained by using transmission measurements through a calibration phantom of known thickness and materials. These methods are independent of CT image reconstruction and bring extra cost. In this study, we propose a parametric physical model based spectrum estimation algorithm for CT. First, a physical model contains six parameters is proposed to represent the x-ray spectrum, which is derived from the x-ray imaging physics. Second, a template image contains different material components can be obtained by segmenting CT reconstructed images with a simple method. And the estimated projection can be calculated by reprojecting the template image with the proposed spectrum model. Finally, the six parameters expressing the spectrum can be solved by minimizing the error between the estimated projection and real measurements. The effectiveness of the proposed method has been validated on the simulated data. Experimental results demonstrate the proposed method can estimate the accurate spectra at low and high energies and provide a good reconstruction of characteristic radiations.
Compared to conventional X-ray transmission imaging techniques, imaging systems based on field-emissive cathode based conformal transmission imaging schemes have smaller volumes. This imaging system combines multiple point sources to complete very low dose imaging of the region of interest using a small cone beam, and finally obtain high quality images by image restoration methods. However, more precise system geometry is required by the system architecture of the new imaging scheme and the special image-forming method. If the geometric parameters that are inconsistent with the actual use are used in image restoration, it will cause the geometric distortion in the final restored image. In this work, a proposed geometric calibration applied to the new imaging scheme. First, we use a partial point source on the periphery of the array ray source to project the side ball phantom of the imaged object. Then, a cost function that associates the geometrical parameters with the degree to which the back-projections of the ball phantom in projections from different point sources is constructed. Finally, the particle swarm optimization (PSO) is used for minimizing the cost function, and the resultant value of the cost function is the actual geometric parameter. With this calibration method, transmission imaging and geometric calibration will be done simultaneously. Besides, this calibration method does not depend on a complex calibration phantom and is simple and effective. In addition, the PSO can accelerate the implementation of the algorithm. The effectiveness and accuracy of this calibration method are verified by two sets of simulation experiments.
4D-CBCT reconstruction technique could provide a sequence of phase-resolved images to alleviate motion blurring artifacts as a result of respiratory movement during CT scanning. However, 4D-CBCT images are degraded by streaking artifacts due to the under-sampled projection used for the reconstruction of each phase. Based on the high correlation of these 4D-CBCT images, estimating the deformation vector fields (DVF) among them via a deformable registration algorithm is one of the possible solutions to improve the image quality. Often, the intensity-based similarity metric is utilized in the optimization problem by minimizing the squared sum of intensity differences (SSD) of the reference image and the target image. However, this metric is not suitable for the 4D-CBCT registration case, because the quality of both the reference image and the target image are not always guaranteed. As a result, the registration accuracy of the conventional SSD metric still has room to improve. In our method, by considering the characteristic of the phase-depended images, we design a novel similarity metric: 1) A prior image reconstructed by the whole projection set is regarded as the reference image; 2) Instead of an intensity-based similarity metric alone, we proposed a free-form based optimization function associating the gradient information in spatial domain with the projection-based constraint. To validate the performance of the proposed method, we carried out a phantom data and a patient data to compare with the classical Demons algorithm. To be specific, the quality of the registered image was improved to a great extent, especially in regions of interest of moving tissues. Quantitative evaluations were shown in terms of the rooted mean square error (RMSE) by our method when compared with existing Demons method.
As an alternative to conventional sources, field emission x-ray cold cathodes of nanomaterials have been developed in recent years. Many different imaging geometries with this kind of source have been proposed, which has the merits of fast response, low energy consumption, and individually addressable switching ability. In this work, we proposed a novel digital tomosynthesis (DTS) geometry based on field emission flat-panel X-ray source array (FEF X-ray source array) and a reconstruction method based on this new geometry. The new DTS with designed lighting mode has shorter acquisition time and lower dose compared with the traditional DTS scheme. Due to the designed lighting mode, it cannot use a traditional reconstruction algorithm. The proposed reconstructed algorithm builds the relation on photons to solve the reconstruction problem. The simulated result shows that the proposed method can obtain 5pl / mm in the X-Y plane and 2pl / mm in the Z plane which indicates the potential of the proposed reconstruction modality.
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