Journal of X-Ray Science and Technology - Volume 29, issue 3

Authors: Kil, Sang Hyeong | Kim, Gyeong Rip | Lee, Moo Seok | Kwak, Jong Hyeok | Lim, Yeong Hyeon | Kim, Gun Do | Lee, Jong Kyu

Article Type: Research Article

Abstract: This study analyzes the response of increasing radiation dose to the pork tenderloin tissue. Considering its significant cell structure, pork tenderloin tissue samples are selected for the experimental objects to measure their electrical impedance characteristics. This study proposes and investigates an effective approach to characterize the variation of the internal change of the components of pork tenderloin tissues caused by radiation. Changes in the pork tenderloin tissues are that the gap of the myotome is more far apart with increase of radiation dose because of the destroyed Myofibrils under the damage. With the increase of radiation dose, the impedance value …of the pork tenderloin tissue decreases. Each of mean differences in the impedance values before and after irradiation dose under 1 Gy, 2 Gy and 4 Gy show 0.55±0.03, 1.09±0.14 and 1.97±0.14, respectively. However, the mean difference substantially increases to 13.08±0.16 at irradiation dose of 10 Gy. Thus, the cell membrane shows the most severe rupture at a radiation dose of 10 Gy. Changes in the microstructure of the irradiated pork tenderloin tissue samples are also checked and validated by a transmission electron microscope. Show more

Keywords: Electrical impedance spectroscopy (EIS), electrical impedance characteristics, radiation exposure, transmission electron microscope (TEM)

DOI: 10.3233/XST-210840

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 383-395, 2021

Authors: Zhu, Zhenyue | Lyu, Shujing | Lu, Yue

Article Type: Research Article

Abstract: BACKGROUND: With the rapid development of deep learning, several neural network models have been proposed for automatic segmentation of prohibited items. These methods usually based on a substantial amount of labelled training data. However, for some prohibited items of rarely appearing, it is difficult to obtain enough labelled samples. Furthermore, the category of prohibited items varies in different scenarios and security levels, and new items may appear from time to time. OBJECTIVE: In order to predict prohibited items with only a few annotated samples and inspect prohibited items of new categories without the requirement of retraining, we introduce …an Attention-Based Graph Matching Network. METHODS: This model applies a few-shot semantic segmentation network to address the issue of prohibited item inspection. First, a pair of graphs are modelled between a query image and several support images. Then, after the pair of graphs are entered into two Graph Attention Units with similarity weights and equal weights, the attentive matching results will be obtained. According to the matching results, the prohibited items can be segmented from the query image. RESULTS: Experiment results and comparison using the Xray-PI dataset and SIXray dataset show that our model outperforms several other state-of-the-art learning models. CONCLUSIONS: This study demonstrates that the similarity loss function and the space restriction module proposed by our model can effectively remove noise and supplement spatial information, which makes the segmentation of the prohibited items on X-ray images more accurate. Show more

Keywords: X-ray images, prohibited item inspection, few-shot semantic segmentation, graph attention mechanism

DOI: 10.3233/XST-210846

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 397-409, 2021

Authors: Sangeetha Francelin Vinnarasi, F. | Daniel, Jesline | Anita Rose, J.T. | Pugalenthi, R.

Article Type: Research Article

Abstract: Multi-modal image fusion techniques aid the medical experts in better disease diagnosis by providing adequate complementary information from multi-modal medical images. These techniques enhance the effectiveness of medical disorder analysis and classification of results. This study aims at proposing a novel technique using deep learning for the fusion of multi-modal medical images. The modified 2D Adaptive Bilateral Filters (M-2D-ABF) algorithm is used in the image pre-processing for filtering various types of noises. The contrast and brightness are improved by applying the proposed Energy-based CLAHE algorithm in order to preserve the high energy regions of the multimodal images. Images from two …different modalities are first registered using mutual information and then registered images are fused to form a single image. In the proposed fusion scheme, images are fused using Siamese Neural Network and Entropy (SNNE)-based image fusion algorithm. Particularly, the medical images are fused by using Siamese convolutional neural network structure and the entropy of the images. Fusion is done on the basis of score of the SoftMax layer and the entropy of the image. The fused image is segmented using Fast Fuzzy C Means Clustering Algorithm (FFCMC) and Otsu Thresholding. Finally, various features are extracted from the segmented regions. Using the extracted features, classification is done using Logistic Regression classifier. Evaluation is performed using publicly available benchmark dataset. Experimental results using various pairs of multi-modal medical images reveal that the proposed multi-modal image fusion and classification techniques compete the existing state-of-the-art techniques reported in the literature. Show more

Keywords: Image fusion, ABF, DCNN, CT, MRI, multi-modal

DOI: 10.3233/XST-210851

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 411-434, 2021

Authors: Yang, Tiejun | Tang, Lu | Tang, Qi | Li, Lei

Article Type: Research Article

Abstract: OBJECTIVE: In order to solve the blurred structural details and over-smoothing effects in sparse representation dictionary learning reconstruction algorithm, this study aims to test sparse angle CT reconstruction with weighted dictionary learning algorithm based on adaptive Group-Sparsity Regularization (AGSR-SART). METHODS: First, a new similarity measure is defined in which Covariance is introduced into Euclidean distance, Non-local image patches are adaptively divided into groups of different sizes as the basic unit of sparse representation. Second, the weight factor of the regular constraint terms is designed through the residuals represented by the dictionary, so that the algorithm takes different smoothing …effects on different regions of the image during the iterative process. The sparse reconstructed image is modified according to the difference between the estimated value and the intermediate image. Last, The SBI (Split Bregman Iteration) iterative algorithm is used to solve the objective function. An abdominal image, a pelvic image and a thoracic image are employed to evaluate performance of the proposed method. RESULTS: In terms of quantitative evaluations, experimental results show that new algorithm yields PSNR of 48.20, the maximum SSIM of 99.06% and the minimum MAE of 0.0028. CONCLUSIONS: This study demonstrates that new algorithm can better preserve structural details in reconstructed CT images. It eliminates the effect of excessive smoothing in sparse angle reconstruction, enhances the sparseness and non-local self-similarity of the image, and thus it is superior to several existing reconstruction algorithms. Show more

Keywords: Adaptive group-sparsity regularization, dictionary learning, spares angle, CT reconstruction

DOI: 10.3233/XST-210839

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 435-452, 2021

Authors: Wu, Zhonghang | Yu, Jieying | Wu, Qianqing | Hou, Pengfei | Sun, Jiuai

Article Type: Research Article

Abstract: BACKGROUND: Virtual radiographic simulation has been found educationally effective for students to practice their clinical examinations remotely or online. A free available virtual simulator-ImaSim has received particular attention for radiographic science education because of its portability, free of charge and no constrain of location and physical facility. However, it lacks evidence to validate this virtual simulation software to faithfully reproduce radiographs comparable to that taken from a real X-ray machine to date. OBJECTIVE: To evaluate image quality of the virtual radiographs produced by the ImaSim. Thus, the deployment of this radiographic simulation software for teaching and experimental studying …of radiography can be justified. METHODS: A real medical X-ray examination machine is employed to scan three standard QC phantoms to produce radiographs for comparing to the corresponding virtual radiographs generated by ImaSim software. The high and low range of radiographic contrast and comprehensive contrast-detail performance are considered to characterize the radiographic quality of the virtual simulation software. RESULTS: ImaSim software can generate radiographs with a contrast ranging from 30% to 0.8% and a spatial resolution as low as 0.6mm under the selected exposure setting condition. The characteristics of contrast and spatial resolution of virtual simulation generally agree with that of real medical X-ray examination machine. CONCLUSION: ImaSim software can be used to simulate a radiographic imaging process to generate radiographs with contrast and detail detectability comparable to those produced by a real X-ray imaging machine. Therefore, it can be adopted as a flexible educational tool for proof of concept and experimental design in radiography. Show more

Keywords: Virtual simulation, density, contrast, image quality

DOI: 10.3233/XST-210860

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 453-462, 2021

Authors: Hu, Chunhong | Zhang, Yu | Xiong, Xing | Meng, Qian | Yao, Feirong | Ye, Aihua | Hao, Zhengmei

Article Type: Research Article

Abstract: OBJECTIVE: To explore the potential value of quantitative parameters derived from dual-energy spectral computed tomography (DESCT) as comparing to the parameters derived from magnetic resonance imaging (MRI) in detecting bone marrow (BM) infiltration and distinguishing different patterns of BM infiltration in patients diagnosed with Multiple myeloma (MM). METHODS: This study involved 35MM patients and 15 healthy control subjects who had undergone spinal DESCT and MRI. Pattern assignment was based on visual assessment of MR images, and the regions of interest were defined on both DESCT and apparent diffusion coefficient maps. Quantitative values of DESCT parameters were measured and …compared between infiltrated and healthy bone marrow. Receiver operating characteristic (ROC) analysis was performed to determine potential utility of DESCT parameters in identifying BM infiltration and different patterns defined by MRI. Sensitivity and specificity under the optimal thresholds determined by the Youden Index were also calculated. RSULTS: Statistical differences were observed between the DESCT parameters including Ca(Water), Water(Ca), HAP(Fat), Fat(HAP) and Effective atomic number (Eff-Z) but not for the 70-keV CT value between the infiltrated and healthy BM (all P  < 0.001). The 70keV CT value and Ca(Water), HAP(Fat) and Eff-Z values were also found to be statistically different in comparing different infiltration patterns (all P  < 0.05). Performance of the model-based parameter Ca/Water was superior in differentiating between infiltrated and healthy BM in which the area under ROC curve, AUC = 0.856 [95% CI, 81.4–89.1%] with sensitivity = 0.841 and specificity = 0.768, as well as between MM patients and control subjects (AUC = 0.910 [95% CI, 79.5–97.3%], sensitivity = 0.829 and specificity = 1.000). CONCLUSIONS: Analysis of DESCT offers potential as a quantitative method to detect infiltrated BM and evaluate infiltration patterns of BM in patients diagnosed with MM. Show more

Keywords: Bone marrow, dual-energy spectral computed tomography (DESCT), multiple myeloma, spectral, vertebra

DOI: 10.3233/XST-200811

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 463-475, 2021

Authors: Xue, Qian | Yang, Xiao-Han | Teng, Gao-Jun | Hu, Shu-Dong

Article Type: Research Article

Abstract: OBJECTIVE: To investigate relationship between the diffusion indexes of corticospinal tract (CST) and the neurological motor outcomes in chronic pontine stroke patients. METHODS: Diffusion tensor imaging (DTI) is performed in 27 patients with chronic pontine stroke. Fractional anisotropy (FA) values along the CST area, the track number, and the CST length are measured. Neurological and motor outcomes are evaluated based on Fugl-meyer (FM), National Institutes of Health Stroke Scale (NIHSS), Barthel index (BI), and modified Rankin scale (mRS) scores. The relationships between FA ratios (rFAs) in the CST of stroke subjects and their clinical motor scores are analyzed …through Spearman’s correlation analysis. Then, diffusion tensor tractography (DTT) is performed to show the injury degree of CST. RESULTS: First, FA values are decreased in the infarct area, cerebral peduncle, posterior limb of the internal capsule, and precentral gyrus compared with those in the contralateral side. The number of CST is decreased in the ipsilateral side of the infarct. Second, rFAs in the cerebral peduncle, posterior limb of the internal capsule, and CST rnum correlate positively with FM scores (r  = 0.824, 0.672, 0.651, p  < 0.001) and negatively with mRS scores (r  = –0.835, –0.604, –0.645, p ≤0.001). Third, the injury degree of CST correlates negatively with FM scores (r  = –0.627, p  < 0.001). CONCLUSIONS: The study demonstrates that rFAs in the cerebral peduncle, posterior limb of the internal capsule, and CST rnum associate with motor outcome, suggesting that DTI may be applicable for outcome evaluation. Show more

Keywords: Corticospinal tract, diffusion tensor imaging, magnetic resonance imaging, pontine stroke

DOI: 10.3233/XST-200817

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 477-489, 2021

Authors: Qiao, Zhiwei

Article Type: Research Article

Abstract: PURPOSE: The adaptive steepest descent projection onto convex set (ASD-POCS) algorithm is a promising algorithm for constrained total variation (TV) type norm minimization models in computed tomography (CT) image reconstruction using sparse and/or noisy data. However, in ASD-POCS algorithm, the existing gradient expression of the TV-type norm appears too complicated in the implementation code and reduces image reconstruction speed. To address this issue, this work aims to develop and test a simple and fast ASD-POCS algorithm. METHODS: Since the original algorithm is not derived thoroughly, we first obtain a simple matrix-form expression by thorough derivation via matrix representations. …Next, we derive the simple matrix expressions of the gradients of TV, adaptive weighted TV (awTV), total p -variation (TpV), high order TV (HOTV) norms by term combinations and matrix representations. The deep analysis is then performed to identify the hidden relations of these terms. RESULTS: The TV reconstruction experiments by use of sparse-view projections via the Shepp-Logan, FORBILD and a real CT image phantoms show that the simplified ASD-POCS (S-ASD-POCS) using the simple matrix-form expression of TV gradient achieve the same reconstruction accuracy relative to ASD-POCS, whereas it enables to speed up the whole ASD process 1.8–2.7 time fast. CONCLUSIONS: The derived simple matrix expressions of the gradients of these TV-type norms may simplify the implementation of the ASD-POCS algorithm and speed up the ASD process. Additionally, a general gradient expression suitable to all the sparse transform-based optimization models is demonstrated so that the ASD-POCS algorithm may be tailored to extended image reconstruction fields with accelerated computational speed. Show more

Keywords: ASD-POCS, total variation, matrix-form expression, TV gradient, image reconstruction

DOI: 10.3233/XST-210858

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 491-506, 2021

Authors: Xu, Lichao | Wang, Shiqin | Wang, Shengping | Wang, Ying | Li, Wentao | Lin, Guangwu | Yuan, Zheng

Article Type: Research Article

Abstract: OBJECTIVES: To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. MATERIALS AND METHODS: Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start of the second course of chemoembolization. Receiver operating characteristic (ROC) curve analysis is performed to evaluate the diagnostic performance and determine optimal cut-off values. Cox regression and Kaplan–Meier survival analyses are used to explore the differences in overall survival (OS) between the responders and …non-responders. RESULTS: The difference is statistically significant in the baseline ADC between the responders and non-responders (P  < 0.001). ROC analyses indicate that the baseline ADC value is a good predictor of response to treatment with an area under the ROC curve (AUC) of 0.744 and the optimal cut-off value of 1.22×10–3  mm2 /s. The Cox regression model shows that the baseline ADC is an independent predictor of OS, with a 57.2% reduction in risk. CONCLUSION: An optimal baseline ADC value is a functional imaging response biomarker that has higher discriminatory power to predict tumor response and prolonged survival following chemoembolization in HCC patients. Show more

Keywords: Chemoembolization, therapeutic, diffusion magnetic resonance imaging, carcinoma, hepatocellular, prognosis, response evaluation criteria in solid tumors

DOI: 10.3233/XST-200827

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 507-516, 2021

Authors: Zhu, Yanan | Pi, Zhian | Zhou, Heping | Li, Zhengjun | Lei, Faqing | Hui, Jianjun | Zhang, Ximeng | Xie, Juanping | Liang, Yukun

Article Type: Research Article

Abstract: OBJECTIVE: To demonstrate the ability of achieving low dose and high-quality head CT images for children with acute head trauma using 100 kVp and adaptive statistical iterative reconstruction (ASIR-V) algorithm in single rotation on a 16 cm wide-detector system. MATERIALS AND METHODS: We retrospectively analyzed the CT dose index (CTDI) and image quality of 104 children aged 0–6 years with acute head trauma (1 hour –3 days) in two groups: Group 1(n  = 50) on a 256-row CT with single rotation at a reduced-dose of 100 kVp/240 mA and reconstructed using ASIR-V at 70%level; Group 2(n  = 54) on a 64-row CT with multiple …rotations at a standard dose of 120 kVp/ 180mA and reconstructed using a conventional filtered back-projection (FBP). Both groups used the 0.5 s/r axial scan mode. CT dose index (CTDI) and quantitative image quality measurements were compared using the Student t test; qualitative image quality comparison was carried out using Mann-Whitney rank test and the inter-reviewer agreement was evaluated using Kappa test. RESULTS: The exposure time was 0.5 s for Group 1 and 3.27±0.29 s for Group 2. The CTDI in Group 1 was 9.74±0.86mGy, 36.38%lower than the 15.31mGy in Group 2 (p  < 0.001). Group 1 and Group 2 had similar artifact index (2.06±1.06 vs. 2.37±1.18) in the cerebellar hemispheres, and similar contrast-to-noise ratio (2.32±0.83 vs. 1.69±0.68), (1.47±0.72 vs. 1.10±0.43) respectively for cerebellum and thalamus (p  > 0.05). Image quality was acceptable for diagnosis, and motion artifacts were reduced in Group 1 (p  < 0.001). CONCLUSION: Single rotation CT with 100 kVp and 70%ASIR-V on 16 cm wide-detector CT reduces radiation dose and motion artifacts for children with acute head trauma without compromising diagnostic quality as compared with standard dose protocol. Thus, it provides a novel imaging method in management of pediatric acute head trauma. Show more

Keywords: Head trauma, adaptive statistical iterative reconstruction, children, wide-detector computed tomography, radiation dose reduction, single rotation

DOI: 10.3233/XST-210856

Citation: Journal of X-Ray Science and Technology, vol. 29, no. 3, pp. 517-527, 2021