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Single grid-based phase-contrast x-ray imaging (g-PCXI) technique, which was recently proposed by Wen et al. to retrieve absorption, scattering, and phase-gradient images from the raw image of the examined object, seems a practical method for phase-contrast imaging with great simplicity and minimal requirements on the setup alignment. In this work, we developed a useful simulation platform for g-PCXI and performed a simulation to demonstrate its viability. We also established a table-top setup for g-PCXI which consists of a focused-linear grid (200-lines/in strip density), an x-ray tube (100-μm focal spot size), and a flat-panel detector (48-μm pixel size) and performed a preliminary experiment with some samples to show the performance of the simulation platform. We successfully obtained phase-contrast x-ray images of much enhanced contrast from both the simulation and experiment and the simulated contract seemed similar to the experimental contrast, which shows the performance of the developed simulation platform. We expect that the simulation platform will be useful for designing an optimal g-PCXI system.

Central venous stenosis is a relatively common complication in hemodialysis patients; however, jugular venous reflux (JVR) and increased intracranial pressure are rare, and associated progressive visual disturbance was reported in only a few cases. Here, we report a case of JVR with visual disturbance and increased intracranial pressure. Notably, the MRI was accompanied by a dilatation of the superior ophthalmic vein, which was mistaken for a cavernous sinus dural arteriovenous fistula (CSdAVF). The patient had JVR on time-of-flight MR angiography (TOF-MRA) and severe stenosis of the left brachiocephalic vein on conventional angiography. After balloon angioplasty for central venous stenosis, he was discharged after improvement of his visual disturbance. Although JVR due to central venous stenosis and CSdAVF might show similar symptoms, treatment plans are different. Therefore, it is important to distinguish radiologically based on a thorough review of MRI and TOF-MRA and confirm the central venous stenosis on cerebral angiography for the accurate diagnosis.

In this paper, we propose a new/next-generation type of CT examinations, the so-called Interior Computed Tomography (ICT), which may presumably lead to dose reduction to the patient outside the target region-of-interest (ROI), in dental x-ray imaging. Here an x-ray beam from each projection position covers only a relatively small ROI containing a target of diagnosis from the examined structure, leading to imaging benefits such as decreasing scatters and system cost as well as reducing imaging dose. We considered the compressed-sensing (CS) framework, rather than common filtered-backprojection (FBP)-based algorithms, for more accurate ICT reconstruction. We implemented a CS-based ICT algorithm and performed a systematic simulation to investigate the imaging characteristics. Simulation conditions of two ROI ratios of 0.28 and 0.14 between the target and the whole phantom sizes and four projection numbers of 360, 180, 90, and 45 were tested. We successfully reconstructed ICT images of substantially high image quality by using the CS framework even with few-view projection data, still preserving sharp edges in the images.

In this work, we propose a practical method that can combine the two functionalities of dental panoramic and cone-beam CT (CBCT) features in one by using a single panoramic detector. We implemented a CS-based reconstruction algorithm for the proposed method and performed a systematic simulation to demonstrate its viability for 3D dental X-ray imaging. We successfully reconstructed volumetric images of considerably high accuracy by using a panoramic detector having an active area of 198.4 mm × 6.4 mm and evaluated the reconstruction quality as a function of the pitch (p) and the angle step (Δθ). Our simulation results indicate that the CS-based reconstruction almost completely recovered the phantom structures, as in CBCT, for p≤2.0 and θ≤6°, indicating that it seems very promising for accurate image reconstruction even for large-pitch and few-view data. We expect the proposed method to be applicable to developing a cost-effective, volumetric dental X-ray imaging system.

In practical applications of three-dimensional (3D) tomographic imaging, there are often challenges for image reconstruction from insufficient sampling data. In computed tomography (CT), for example, image reconstruction from sparse views and/or limited-angle (

The most popular reconstruction algorithm for cone-beam computed tomography (CBCT) is based on the computationally-inexpensive filtered-backprojection (FBP) method. However, that method usually requires dense projections over the Nyquist samplings, which imposes severe restrictions on the imaging doses. Moreover, the algorithm tends to produce cone-beam artifacts as the cone angle is increased. Several variants of the FBP-based algorithm have been developed to overcome these difficulties, but problems with the cone-beam reconstruction still remain. In this study, we considered a compressed-sensing (CS)-based reconstruction algorithm for low-dose, high-quality dental CBCT images that exploited the sparsity of images with substantially high accuracy. We implemented the algorithm and performed systematic simulation works to investigate the imaging characteristics. CBCT images of high quality were successfully reconstructed by using the built-in CS-based algorithm, and the image qualities were evaluated quantitatively in terms of the universal-quality index (UQI) and the slice-profile quality index (SPQI).We expect the reconstruction algorithm developed in the work to be applicable to current dental CBCT systems, to reduce imaging doses, and to improve the image quality further.

In the paper, we proposed a pragmatic method capable of implementing a cost-effective, low-dose CT reconstruction directly onto a dental panoramic X-ray imaging system by adopting a spiral source trajectory. In the proposed geometry, a linear-type panoramic imaging sensor is rotated 90° from the orientation for panoramic imaging to imitate fan-beam image acquisition. For image reconstruction, we considered a total variation (TV) minimization-based algorithm that exploited the sparsity of the image gradient and was capable of reconstructing CT images with substantially high image accuracy against the image artifacts from sparse-view data. We implemented the algorithm for the proposed geometry and performed systematic simulation works to demonstrate its feasibility for dental imaging applications. CT images were successfully reconstructed from the proposed geometry, and the reconstruction quality was evaluated quantitatively by using an image similarity metric. We expect the proposed method to be applicable to developing a cost-effective, low-dose, all-in-one dental imaging system.

In this paper, we introduce limited-angle tomography in which the object being imaged is rotated around the center of an inclined X-ray beam, the so-called micro-DTS (digital tomosynthesis), with a few-view image reconstruction based on the compressed-sensing (CS) theory for applications of fast, low-dose X-ray imaging. We implemented an effective CS-based reconstruction algorithm for micro-DTS and performed systematic simulation works. The assessment of the image characteristics was performed by using several figures of merit such as the root-mean-square error (RMSE), the contrast-to-noise ratio (CNR), and the universal image-quality index (UQI) to compare the reconstructed images to the simulated phantoms. According to our results, compared to the FBP-based method, the CS-based reconstruction method substantially enhanced image accuracy against image artifacts from few-view and limited-angle projections. In the simulation, 41 projections were used for the half-tomographic angles of 30°, 45°, and 60°, giving UQI values of 0.92 ∼ 0.97, which seems promising for potential applications of fast, low-dose X-ray imaging.

Panoramic radiography with which only structures within a certain image layer are in focus and others out of focus on the panoramic image has become a popular imaging technique especially in dentistry. However, the major drawback to the technique is a mismatch between the structures to be focused and the predefined image layer mainly due to the various shapes and sizes of dental arches and/or to malpositioning of the patient. These result in image quality typically inferior to that obtained using intraoral radiographic techniques. In this paper, to overcome these difficulties, we suggest a new panoramic reconstruction algorithm, the so-called adaptive panoramic tomography (APT), capable of reconstructing multifocal image layers with no additional exposure. In order to verify the effectiveness of the proposed algorithm, we performed systematic simulation studies with a circular rotational movement and investigated the image performance.