Journal of X-Ray Science and Technology - Volume 26, issue 2
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Impact Factor 2020: 1.342
Journal of X-Ray Science and Technology is an international journal designed for the diverse community (biomedical, industrial and academic) of users and developers of novel x-ray imaging techniques. The purpose of the journal is to provide clear and full coverage of new developments and applications in the field.
Areas such as x-ray microlithography, x-ray astronomy and medical x-ray imaging as well as new technologies arising from fields traditionally considered unrelated to x rays (semiconductor processing, accelerator technology, ionizing and non-ionizing medical diagnostic and therapeutic modalities, etc.) present opportunities for research that can meet new challenges as they arise.
Abstract: The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features,…we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). By comparing three types of CNN models in which two of them were newly proposed by us, we observed that the multi-channel CNN model yielded the best discrimination in capacity of differentiating malignancy risk of the nodules based on the projection of distributions of extracted features. Moreover, CADx scheme using the new multi-channel CNN model outperformed our previously developed CADx scheme using the 3D texture feature analysis method, which increased the computed area under a receiver operating characteristic curve (AUC) from 0.9441 to 0.9702.
Abstract: BACKGROUND: Four-dimensional cone beam computed tomography allows for temporally resolved imaging with useful applications in radiotherapy, but raises particular challenges in terms of image quality and computation time. OBJECTIVE: The purpose of this work is to develop a fast and accurate 4D algorithm by adapting a GPU-accelerated ordered subsets convex algorithm (OSC), combined with the total variation minimization regularization technique (TV). METHODS: Different initialization schemes were studied to adapt the OSC-TV algorithm to 4D reconstruction: each respiratory phase was initialized either with a 3D reconstruction or a blank image. Reconstruction algorithms were tested on a dynamic…numerical phantom and on a clinical dataset. 4D iterations were implemented for a cluster of 8 GPUs. RESULTS: All developed methods allowed for an adequate visualization of the respiratory movement and compared favorably to the McKinnon-Bates and adaptive steepest descent projection onto convex sets algorithms, while the 4D reconstructions initialized from a prior 3D reconstruction led to better overall image quality. CONCLUSION: The most suitable adaptation of OSC-TV to 4D CBCT was found to be a combination of a prior FDK reconstruction and a 4D OSC-TV reconstruction with a reconstruction time of 4.5 minutes. This relatively short reconstruction time could facilitate a clinical use.
Abstract: BACKGROUND: Since breast ultrasound images are of low contrast, contain inherent noise and shadowing effect due to its imaging process, segmentation of breast tumors depicting ultrasound image is a challenging task. Thus, a robust breast ultrasound image segmentation technique is inevitable. OBJECTIVE: To develop an automatic lesion segmentation technique for breast ultrasound images. METHODS: First, the technique automatically detects the suspicious tumor region of interest and discards the unwanted complex background regions. Next, based on the concept of information gain, the technique applies an existing neutrosophic clustering method to the detected region to segment the desired…tumor area. The proposed technique computes information gain values from the local neighbourhood of each pixel, which is further used to update the membership values and the cluster centers for the neutrosophic clustering process. Integrating the concept of entropy and neutrosophic logic features into the technique enabled to generate better segmentation results. RESULTS: Results of proposed method were compared both qualitatively and quantitatively with fuzzy c-means, neutrosophic c-means and neutrosophic ℓ-means clustering methods. It was observed that the proposed method outperformed the other three methods and yielded the best Mean (TP: 94.72, FP: 5.85, SI: 93.75, HD: 8.2, AMED: 2.4) and Standard deviation (TP: 3.2, FP: 3.7, SI: 3.8, HD: 2.6, AMED: 1.3) values for different quality metrics on the current set of breast ultrasound images. CONCLUSION: Study demonstrated that the proposed technique is robust to the shadowing effect and produces more accurate segmentation of the tumor region, which is very similar to that visually segmented by Radiologist.
Keywords: Ultrasound images, breast tumor, fuzzy c-means clustering, neutrosophic clustering, information gain
Abstract: This study aims to investigate and test a new image reconstruction algorithm applying to the low-signal projections to generate high quality images by reducing the artifacts and noise in the cone-beam computed tomography (CBCT). For the low-signal and noisy projections, a multiple sampling method is first utilized in projection domain to suppress environmental noise, which guarantees the accuracy of the data for reconstruction, simultaneously. Next, a fuzzy entropy based method with block matching 3D (BM3D) filtering algorithm is employed to improve the image quality to reduce artifacts and noise in image domain. Then, simulation studies on polychromatic spectrum were performed…to evaluate the performance of the proposed new algorithm. Study results demonstrated significant improvement in the signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of the images reconstructed using the new algorithm. SNRs and CNRs of the new images were averagely 40% and 20% higher than those of the previous images reconstructed using the traditional algorithms, respectively. As a result, since the new image reconstruction algorithm effectively reduced the artifacts and noise, and produced images with better contour and grayscale distribution, it has the potential to improve image quality using the original CBCT data with the low and missing signals.
Abstract: For cone-beam computed tomography (CBCT), transversal shifts of the rotation center exist inevitably, which will result in geometric artifacts in CT images. In this work, we propose a novel geometric calibration method for CBCT, which can also be used in micro-CT. The symmetry property of the sinogram is used for the first calibration, and then L0-norm of the gradient image from the reconstructed image is used as the cost function to be minimized for the second calibration. An iterative search method is adopted to pursue the local minimum of the L0-norm minimization problem. The transversal shift value is updated with…affirmatory step size within a search range determined by the first calibration. In addition, graphic processing unit (GPU)-based FDK algorithm and acceleration techniques are designed to accelerate the calibration process of the presented new method. In simulation experiments, the mean absolute difference (MAD) and the standard deviation (SD) of the transversal shift value were less than 0.2 pixels between the noise-free and noisy projection images, which indicated highly accurate calibration applying the new calibration method. In real data experiments, the smaller entropies of the corrected images also indicated that higher resolution image was acquired using the corrected projection data and the textures were well protected. Study results also support the feasibility of applying the proposed method to other imaging modalities.
Keywords: CBCT, geometric artifact, rotation center shift, L0-norm, FDK
Abstract: BACKGROUND: Mono-capillary optics have been applied to increase the performance of X-ray instruments. However, performance of a mono-capillary optic strongly depends on the shape accuracy, which is determined by the diameters of the inner hollow of the capillary along the axial direction. OBJECTIVE: To precisely determine the inner diameter of the capillary optic used in X-ray imaging technique, which aims to replace the conventional method using a visible microscope. METHODS: High spatial resolution X-ray images of the mono-capillary optic were obtained by a synchrotron radiation beamline. The inner diameter of the mono-capillary optic was measured and…analyzed by the pixel values of the X-ray image. RESULT: Edge enhancement effect was quite useful in determining the inner diameter, and the accuracy of the diameter determination was less than 1.32 μm. Many images obtained by scanning the mono-capillary optic along the axial direction were combined, and the axial profile, consisting of diameters along the axial direction, was obtained from the combined image. The X-ray imaging method could provide an accurate measurement with slope error of±19 μrad. CONCLUSIONS: Applying X-ray imaging technique to determine the inner diameter of a mono-capillary optic can contribute to increasing fabrication accuracy of the mono-capillary optic through a feedback process between the fabrication and measurement of its diameter.
Abstract: BACKGROUND: Anti-scattering grid has been used to improve the image quality. However, applying a commonly used linear or parallel grid would cause image distortion, and focusing grid also requires a precise fabrication technology, which is expensive. OBJECTIVE: To investigate and analyze whether using CO2 laser micromachining-based PMMA anti-scattering grid can improve the performance of the grid at a lower cost. Thus, improvement of grid performance would result in improvement of image quality. METHODS: The cross-sectional shape of CO2 laser machined PMMA is similar to alphabet ‘V’. The performance was characterized by contrast improvement factor…(CIF) and Bucky. Four types of grid were tested, which include thin parallel, thick parallel, ‘V’-type and ‘inverse V’-type of grid. RESULTS: For a Bucky factor of 2.1, the CIF of the grid with both the “V” and inverse “V” had a value of 1.53, while the thick and thick parallel types had values of 1.43 and 1.65, respectively. CONCLUSION: The ‘V’ shape grid manufacture by CO2 laser micromachining showed higher CIF than parallel one, which had same shielding material channel width. It was thought that the ‘V’ shape grid would be replacement to the conventional parallel grid if it is hard to fabricate the high-aspect-ratio grid.
Abstract: OBJECTIVES: To evaluate the potential privileges of flattening filter-free (FFF) photon beams from Oncor® linac for 6 MV and 18 MV energies. METHODS: A Monte Carlo (MC) model of Oncor® linac was built using BEAMnrc MCCode and verified by the measured data using 6 MV and 18 MV energies. A comprehensive set of data was also characterized for MC model of Oncor® machine running with and without flattening filter (FF) for 6 MV and 18 MV beams in six field sizes. The investigated characteristics included mean energy, energy spectrum, photon spatial fluence, superficial dose, percent depth dose (PDD), dose output, and…out-of-field dose with two indexes of lateral dose profile and isodose curve at three depths. RESULTS: Using FFF enhanced the energy uniformity 3.4±0.11% (6 MV) and 2.05±0.09% (18 MV) times and improved dose output by factor of 2.91 (6 MV) and 4.2 (18 MV) on the central axis, respectively. Using FFF also reduced the PDD dependencies by 9.1% (6 MV) and 5.57% (18 MV). In addition, using FFF had a lower out-of-field dose due to the reduced head scatter and softer spectra. CONCLUSIONS: The findings in this study suggested that using FFF, Oncor® machine could achieve better treatment results with lower dose toxicity and a shorter beam-on time.
Keywords: Radiation therapy, medical linear accelerator, flattening filter, Monte Carlo calculations, BEAMnrc, Monte Carlo code
Abstract: Active x-ray collimation is well adopted in radiography and fluoroscopy for radiation dose reduction and image quality improvement. The application of this concept in computed tomography (CT) is significantly limited due to the truncation of projection data. Generally, an internal field of view (FOV) inside an imaging object cannot be exactly reconstructed only from the truncated projection data. Recent research shows that given some prior information of the FOV image, interior tomography can provide a unique and stable solution for image reconstruction of an internal FOV. The objective of this study is to evaluate the performance of interior reconstruction based…on patient datasets obtained from a clinical CT scanner with dual x-ray tubes, which simultaneously gives full projections and truncated projections. Image reconstructions are performed from full and truncated projection data for the comparison of image quality, respectively. The reconstructed CT images were reviewed by a radiologist and a resident. The evaluation results of two observers showed that CT images reconstructed with truncated projections met clinically diagnostic requirements and were comparable to clinical images. This study demonstrates that with the development of interior tomography, active x-ray collimation in the imaging plane can be readily employed in CT imaging to further reduce patient radiation and improve image quality.
Keywords: Active x-ray collimation, computed tomography (CT) image reconstruction, internal field of view in CT images, interior tomography
Abstract: Dual energy computed tomography (DECT) can improve the capability of differentiating different materials compared with conventional CT. However, due to non-negligible radiation exposure to patients, dose reduction has recently become a critical concern in CT imaging field. In this work, to reduce noise at the same time maintain DECT images quality, we present an iterative reconstruction algorithm for low-dose DECT images where in the objective function of the algorithm consists of a data-fidelity term and a regularization term. The former term is based on alpha-divergence to describe the statistical distribution of the DE sinogram data. And the latter term is…based on the redundant information to reflect the prior information of the desired DECT images. For simplicity, the presented algorithm is termed as “AlphaD-aviNLM”. To minimize the associative objective function, a modified proximal forward-backward splitting algorithm is proposed. Digital phantom, physical phantom, and patient data were utilized to validate and evaluate the presented AlphaD-aviNLM algorithm. The experimental results characterize the performance of the presented AlphaD-aviNLM algorithm. Speficically, in the digital phantom study, the presented AlphaD-aviNLM algorithm performs better than the PWLS-TV, PWLS-aviNLM, and AlphaD-TV with more than 49%, 34%, and 40% gains for the RMSE metric, 1.3%, 0.4%, and 0.7% gains for the FSIM metric and 13%, 8%, and 11% gains for the PSNR metric. In the physical phantom study, the presented AlphaD-aviNLM algorithm performs better than the PWLS-TV, PWLS-aviNLM, and AlphaD-TV with more than 0.55%, 0.07%, and 0.16% gains for the FSIM metric.
Keywords: Dual energy computed tomography, low-dose, renconstruction, alpha-divergence, redundant information