Journal of X-Ray Science and Technology - Volume 24, issue 3
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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: Single-scattered X-ray doses at 1 m from silicon, copper and lead targets were calculated using an analytical point-kernel method considering the self-absorption, and the calculated values were compared with detailed results of a Monte Carlo calculation with respect to the emission angle. In the calculations, a slab slanted at 3° to the beam axis was used for silicon in addition to the cylindrical targets for the three materials, and the slab geometry showed the largest doses. The analytical calculations were underestimated compared with the Monte Carlo calculations by less than 24% for silicon and 40% for copper, particularly at large-angle scattering,…which was attributable to the buildup effect of the single-scattered X-rays in the targets. By considering the buildup effect, the difference from Monte Carlo results decreased to less than 20%. For lead, the influence of fluorescent X-rays produced by the source beam was dominant in the backward direction, which was also calculated analytically. The simple analytical program can be applied to any target size and shape by considering self-absorption and the buildup effect, both of which inform the simple dose estimation method.
Keywords: X-ray beam, self-absorption, buildup effect, Monte Carlo, point-kernel method
Abstract: BACKGROUND: Coronary artery disease (CAD) remains the leading cause of death worldwide. Currently, cardiac multi-detector computed tomography (MDCT) is widely used to diagnose CAD. The purpose in this study is to identify informative and useful predictors from left ventricular (LV) in the early CAD patients using cardiac MDCT images. MATERIALS AND METHODS: Study groups comprised 42 subjects who underwent a screening health examination, including laboratory testing and cardiac angiography by 64-slice MDCT angiography. Two geometrical characteristics and one image density were defined as shape, size and stiffness on MDCT image. The t-test, logistic regression, and receiver operating…characteristic curve were applied to assess and identify the significant predictors. The Kappa statistics was used to exam the agreements with physician’s judgments (i.e., Golden of True, GOT). RESULTS: The proposed three characteristics of LV MDCT images are important predictors and risk factors for the early CAD patients. These predictors present over 80% of AUC and higher odds ratio. The Kappa statistics was 0.68 for the combinations of shape and stiffness into logistic regression. CONCLUSIONS: The shape, size and stiffness of the left ventricular on MDCT can be used to be the effective indicators in the early CAD patients. Besides, the combinations of shape and stiffness into logistic regression could provide substantial agreement with physician’s judgments.
Keywords: MDCT, early CAD, geometrical characteristics, image density
Abstract: BACKGROUND: Patient dose from image guidance in radiotherapy is small compared to the treatment dose. However, the imaging beam is untargeted and deposits dose equally in tumor and healthy tissues. It is desirable to minimize imaging dose while maintaining efficacy. OBJECTIVE: Image guidance typically does not require full image quality throughout the patient. Dynamic filtration of the kV beam allows local control of CT image noise for high quality around the target volume and lower quality elsewhere, with substantial dose sparing and reduced scatter fluence on the detector. METHODS: The dynamic Intensity-Weighted Region of Interest…(dIWROI) technique spatially varies beam intensity during acquisition with copper filter collimation. Fluence is reduced by 95% under the filters with the aperture conformed dynamically to the ROI during cone-beam CT scanning. Preprocessing to account for physical effects of the collimator before reconstruction is described. RESULTS: Reconstructions show image quality comparable to a standard scan in the ROI, with higher noise and streak artifacts in the outer region but still adequate quality for patient localization. Monte Carlo modeling shows dose reduction by 10-15% in the ROI due to reduced scatter, and up to 75% outside. CONCLUSIONS: The presented technique offers a method to reduce imaging dose by accepting increased image noise outside the ROI, while maintaining full image quality inside the ROI.
Keywords: Region of interest imaging, image guidance, IGRT, cone-beam CT
Abstract: Grating based X-ray differential phase contrast imaging (DPCI) allows for high contrast imaging of materials with similar absorption characteristics. In the last years’ publications, small animals or parts of the human body like breast, hand, joints or blood vessels have been studied. Larger objects could not be investigated due to the restricted field of view limited by the available grating area. In this paper, we report on a new stitching method to increase the grating area significantly: individual gratings are merged on a carrier substrate. Whereas the grating fabrication process is based on the LIGA technology (X-ray lithography and electroplating)…different cutting and joining methods have been evaluated. First imaging results using a 2×2 stitched analyzer grating in a Talbot-Lau interferometer have been generated using a conventional polychromatic X-ray source. The image quality and analysis confirm the high potential of the stitching method to increase the field of view considerably.
Keywords: X-ray phase contrast imaging, talbot interferometry, field of view, grating, LIGA, stitching
Abstract: In the current paper we consider the Helical Cone Beam CT. This scanning method exposes the patient to large quantities of radiation and results in very large amounts of data being collected and stored. Both these facts are prime motivators for the development of an efficient, reduced rate, sampling pattern. We calculate bounds on the support in the frequency domain of the collected data and use these to suggest an efficient sampling pattern. A reduction of up to a factor of 2 in sampling rate is suggested. Indeed, we show that reconstruction quality is not affected by this reduction of…sampling rates.
Abstract: X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today’s clinical dual energy CT scanners usually measure different rays for different energy spectra…and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.
Keywords: Dual energy computed tomography, basis material decomposition, image quality
Abstract: The article describes the X-ray fluorescence (XRF) studies on the chemical composition of archaeological artefacts. The mapping of the concentration of selected elements has been used to recognise the way of object production and the use. The obtained data allowed to obtain the new information, which is impossible to gain by use of different methods. ‘The data obtained from the chemical composition of the particular parts of the objects may be used for the interpretation of the manufacturing technology or the primal form of the objects. Additionally, the knowledge obtained from the chemical composition of the different parts of the…artefacts may be essential for the selection of the protection and conservation methods. The present studies can be useful to improve knowledge about the level of former craftsmanship. These knowledge allow us to exam archaeological artefacts in a new light, and these findings can also broaden the archaeological knowledge horizons and provide good bases for further detailed studies.
Abstract: Tumor tracking is performed during patient set-up and monitoring of respiratory motion in radiotherapy. In the clinical setting, there are several types of equipment for this set-up such as the Electronic Portal imaging Device (EPID) and Cone Beam CT (CBCT). Technically, an optical positioning system tracks the difference between the infra ball reflected from body and machine isocenter. Our objective is to compare the clinical positioning error of patient setup between Cone Beam CT (CBCT) with the Optical Positioning System (OPS), and to evaluate the traditional positioning systems and OPS based on our proposed approach of patient positioning. In our…experiments, a phantom was used, and we measured its setup errors in three directions. Specifically, the deviations in the left-to-right (LR), anterior-to-posterior (AP) and inferior-to-superior (IS) directions were measured by vernier caliper on a graph paper using the Varian Linear accelerator. Then, we verified the accuracy of OPS based on this experimental study. In order to verify the accuracy of phantom experiment, 40 patients were selected in our radiotherapy experiment. To illustrate the precise of optical positioning system, we designed clinical trials using EPID. From our radiotherapy procedure, we can conclude that OPS has higher precise than conventional positioning methods, and is a comparatively fast and efficient positioning method with respect to the CBCT guidance system.
Abstract: Purpose: The purpose of this study was to compare the dosimetric characteristics for protection of the hippocampus between dual arc VMAT (volumetric modulated arc therapy) and 7 fields intensity-modulated radiation therapy (7F-IMRT) for patients with brain metastases from lung cancer under the whole brain radiotherapy. Methods: Based on ten cases with brain metastases from lung cancer, two types of radiotherapy plans were designed, namely, dual arc VMAT and 7F-IMRT. Provided that the clinical requirements were satisfied, the comparisons of target dose distribution, conformity index (CI), homogeneity index (HI), dose of organs at risk (OARs), monitor units (MU)…and treatment time between dual arc VMAT and 7F-IMRT were investigated for their dosimetric difference. Results: Both treatment plans met the requirements of clinical treatments. However, the PTV-HA conformity and homogeneity of dual arc VMAT were superior to those of 7F-IMRT (P < 0.05). As to OARs, the mean maximum doses (Dmax ) of hippocampus, eyes and optic nerves in the dual arc VMAT plan were all lower than those in 7F-IMRT plan (P < 0.05), but the result had no statistical significance (P < 0.05) for the maximum dose of lens. Compared with 7F-IMRT, dual arc VMAT reduced the average number of MU by 67% and the average treatment time by 74%. Therefore, treatment time was shortened by dual arc VMAT. Conclusion: With regards to the patients with brain metastases from lung cancer under the whole brain radiotherapy, the PTV-HA conformity and homogeneity of dual arc VMAT were superior to those of 7F-IMRT under the precise of meeting the clinical requirements. In addition, dual arc VMAT remarkably reduced the irradiation dose to OARs (hippocampus, eyes and optic nerves), MU and treatment time, as well, guaranteed patients with better protection.
Abstract: Pattern classification has been increasingly used in functional magnetic resonance imaging (fMRI) data analysis. However, the classification performance is restricted by the high dimensional property and noises of the fMRI data. In this paper, a new feature selection method (named as “NMI-F”) was proposed by sequentially combining the normalized mutual information (NMI) and fisher discriminant ratio. In NMI-F, the normalized mutual information was firstly used to evaluate the relationships between features, and fisher discriminant ratio was then applied to calculate the importance of each feature involved. Two fMRI datasets (task-related and resting state) were used to test the proposed method.…It was found that classification base on the NMI-F method could differentiate the brain cognitive and disease states effectively, and the proposed NMI-F method was prior to the other related methods. The current results also have implications to the future studies.
Keywords: Pattern classification, feature selection, functional magnetic resonance imaging (fMRI), normalized mutual information (NMI), fisher discriminant ratio
Abstract: Non-local means algorithm can remove image noise in a unique way that is contrary to traditional techniques. This is because it not only smooths the image but it also preserves the information details of the image. However, this method suffers from high computational complexity. We propose a multi-scale non-local means method in which adaptive multi-scale technique is implemented. In practice, based on each selected scale, the input image is divided into small blocks. Then, we remove the noise in the given pixel by using only one block. This can overcome the low efficiency problem caused by the original non-local means…method. Our proposed method also benefits from the local average gradient orientation. In order to perform evaluation, we compared the processed images based on our technique with the ones by the original and the improved non-local means denoising method. Extensive experiments are conducted and results shows that our method is faster than the original and the improved non-local means method. It is also proven that our implemented method is robust enough to remove noise in the application of neuroimaging.
Keywords: Non-local means, denoising, adaptive multi-scale, average gradient orientation, neuroimaging
Abstract: Brain tissue segmentation from magnetic resonance (MR) images is an importance task for clinical use. The segmentation process becomes more challenging in the presence of noise, grayscale inhomogeneity, and other image artifacts. In this paper, we propose a robust kernelized local information fuzzy C-means clustering algorithm (RKLIFCM). It incorporates local information into the segmentation process (both grayscale and spatial) for more homogeneous segmentation. In addition, the Gaussian radial basis kernel function is adopted as a distance metric to replace the standard Euclidean distance. The main advantages of the new algorithm are: efficient utilization of local grayscale and spatial information, robustness…to noise, ability to preserve image details, free from any parameter initialization, and with high speed as it runs on image histogram. We compared the proposed algorithm with 7 soft clustering algorithms that run on both image histogram and image pixels to segment brain MR images. Experimental results demonstrate that the proposed RKLIFCM algorithm is able to overcome the influence of noise and achieve higher segmentation accuracy with low computational complexity.
Keywords: Brain tissue segmentation, magnetic resonance images, fuzzy C-means, grayscale and spatial information, Gaussian radial basis kernel, image histogram