Journal of X-Ray Science and Technology - Volume 27, issue 5
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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: OBJECTIVE: Radiogenomics investigates radiographic imaging phenotypes associated with gene expression patterns. This study aims to explore relationships between CT imaging radiomics features and gene expression data in non-small cell lung cancer (NSCLC). METHODS: Eighty-nine NSCLC patients are included in the study. Radiomics features are extracted and selected to quantify the phenotype of tumors on CT-scans. Co-expressed genes are also clustered and the first principal component of the cluster is represented, which is defined as a metagene. Then, statistical analysis was performed to assess association of CT radiomics features with metagenes. In addition, predictive models are built and metagene…enrichment are conducted to further evaluate performance of NSCLC radiogenomics statistically and biologically. RESULTS: There are 187 significant pairwise correlations between a CT radiomics feature and a metagene of NSCLC, where eighteen metagenes are annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. Metagenes are predicted in terms of radiomics features with an accuracy of 41.89% –89.93%. CONCLUSIONS: This study reveals the associations between CT imaging radiomics features and NSCLC co-expressed gene sets. The findings suggest that CT radiomics features can reflect important biological information of NSCLC patients, which may have a significant clinical impact as CT is routinely used in clinical practice, assisting in improving medical decision-support at low cost.
Keywords: Radiogenomics, radiomics features, computed tomography, non-small cell lung cancer
Abstract: BACKGROUND: Iterative reconstruction is well-established in diagnostic multidetector computed tomography (MDCT) for dose reduction and image quality enhancement. Its application to diagnostic cone beam computed tomography (CBCT) is only emerging and warrants a quantitative evaluation. METHODS: Several phantoms and a canine head specimen were imaged using a commercially available small-field CBCT scanner. Raw projection data were reconstructed using the Feldkamp-Davis-Kress (FDK) method with different filters, including denoising via total variation (TV) minimization (FDK-TV). Iterative reconstruction was carried out using the TV-regularized ordered subsets convex technique (OSC-TV). Signal-to-noise ratio (SNR), noise power spectrum (NPS) and spatial resolution of images…were estimated. Dose levels were measured via the weighted computed tomography dose index, while low-dose image quality degradation was estimated via structural similarity (SSIM). RESULTS: OSC-TV and FDK-TV were shown to significantly improve image signal-to-noise ratio (SNR) compared to FDK with a standard filter, 5.8 and 4.0 times, respectively. Spatial resolution attained with different algorithms varied moderately across different experiments. For low-dose acquisitions, image quality decreased dramatically for FDK but not for FDK-TV nor OSC-TV. For low-dose canine head images acquired using about 1/5 of the dose compared to a reference image, SSIM dropped to about 0.3 for FDK, while remaining at 0.92 for FDK-TV and 0.96 for OSC-TV. CONCLUSION: OSC-TV was shown to improve image quality compared to FDK and FDK-TV. Moreover, this iterative approach allowed for significant dose reduction while maintaining image quality.
Abstract: BACKGROUND: Segmentation of prostate from magnetic resonance images (MRI) is a critical process for guiding prostate puncture and biopsy. Currently, the best results are obtained by Convolutional Neural Network (CNN). However, challenges still exist when applying CNN to segment prostate, such as data distribution issue caused by insubstantial and inconsistent intensity levels and vague boundaries in MRI. OBJECTIVE: To segment prostate gland from a MRI dataset including different prostate images with limited resolution and quality. METHODS: We propose and apply a global histogram matching approach to make intensity distribution of the MRI dataset closer to uniformity.…To capture the real boundaries and improve segmentation accuracy, we employ a module of variational models to help improve performance. RESULTS: Using seven evaluation metrics to quantify improvements of our proposed fusion approach compared with the state of art V-net model resulted in increase in the Dice Coefficient (11.2%), Jaccard Coefficient (13.7%), Volumetric Similarity (12.3%), Adjusted Rand Index (11.1%), Area under ROC Curve (11.6%), and reduction of the Mean Hausdorff Distance (16.1%) and Mahalanobis Distance (2.8%). The 3D reconstruction also validates the advantages of our proposed framework, especially in terms of smoothness, uniformity, and accuracy. In addition, observations from the selected examples of 2D visualization show that our segmentation results are closer to the real boundaries of the prostate, and better represent the prostate shapes. CONCLUSIONS: Our proposed approach achieves significant performance improvements compared with the existing methods based on the original CNN or pure variational models.
Abstract: BACKGROUND: Breast cancer has the highest cancer prevalence rate among the women worldwide. Early detection of breast cancer is crucial for successful treatment and reducing cancer mortality rate. However, tumor detection of breast ultrasound (US) image is still a challenging work in computer-aided diagnosis (CAD). OBJECTIVE: This study aims to develop a novel automated algorithm for breast tumor detection based on deep learning. METHODS: We proposed a new deep learning network named One-step model which have one input and two outputs, the first one was the segmentation result and the other one was used for false-positive…reduction. The proposed One-step model includes three key components: Base-net, Seg-net, and Cls-net based on Anchor Box. The model chose DenseNet to construct Base-net, the decoder part of RefineNet as Seg-net, and connected several middle layers of Base-net and Seg-net to Cls-net. From the first output acquired by Base-net and Seg-net, the model detected a series of suspicious lesion regions. Then the second output from the Cls-net was used to recognize and reduce the false-positive regions. RESULTS: Experimental results showed that the new model achieved competitive detection result with 90.78% F1 score, which was 8.55% higher than Single Shot MultiBox Detector (SSD) method. In addition, running new model is also computational efficient and has comparative cost effect as SSD. CONCLUSIONS: We established a novel One-step model which improves location accuracy by generating more precise bounding box via Seg-net and removing false targets by another object detection network (Cls-net). On the other hand, a real-time detection of tumor is achieved by sharing the common Base-net. The experimental results showed that the new model performed well on various irregular and blurred ultrasound images. As a result, this study demonstrated feasibility of applying deep learning scheme to detect breast lesions depicting on US image.
Keywords: Automatic location, breast tumor, deep learning, fully connected convolutional networks, segmentation, ultrasound image, Anchor Box
Abstract: Anomalously high x-ray scattering at a wavelength of 0.154 nm by super-polished substrates of fused silica, which were etched by the argon ions with the energy of 300 eV, is detected. The scattering intensity increases monotonically with increasing of the etching depth. The effect is explained by the scattering on the volume inhomogeneities with the lateral size greater than 0.5 μm of the subsurface “damaged” layer. The concentration of volume inhomogeneities increases with the increase of the fluence of argon ions, but the concentration of implanted argon atoms in the layer quickly reaches the maximum value and then begins a trend of…going down. The thickness of the “damaged” layer is approximately equal to the penetration depth of the Ar atoms and can be directly determined from the x-ray specular reflection. It is shown that the presence of volume inhomogeneities of the subsurface “damaged” layer does not affect the geometric roughness of the surface. The observed effect imposes limitations on the usage of grazing incidence x-ray optics without reflective coatings and of the diffuse x-ray scattering (DXRS) method for studying the substrate roughness. A new method that potentially enables to evaluate the applicability of the DXRS method in practice is proposed.
Keywords: X-ray optics, X-Ray diffuse scattering, supersmooth surface, Ion polishing, Roughness, Ion implantation
Abstract: OBJECTIVE: This study aims to assess the value of ultrasound real-time shear wave elastography (US-SWE) for evaluation of nonalcoholic fatty liver disease (NAFLD) in a rabbit model compared with multislice computed tomography (MSCT). MATERIAL AND METHODS: Twenty-six rabbits were fed with high-fat, high-cholesterol diet and six rabbits were fed with a standard diet. All rabbits were performed with MSCT and US-SWE at various time points to measure changes in liver parenchyma. The diagnostic efficiency of US-SWE was analyzed using receiver operating characteristics (ROC) curves compared with MSCT based on the liver pathology. RESULTS: The statistically significant…differences in the areas under the ROC curves between using MSCT and US-SWE modalities were detected to discriminate between normal vs. NAFLD or higher severity pathology. Similarly, for normal or NAFLD vs. borderline or NASH livers, statistically significant differences between using US-SWE and MSCT modalities were also detected for nonalcoholic steatohepatitis (NASH) vs. lower severity pathology. CONCLUSIONS: MSCT, but not US-SWE, had a better ability to differentiate normal or NAFLD livers from higher severity NAFLD livers. However, the diagnostic efficiency of US-SWE was superior to that of MSCT for differentiating NASH from normal or lower severity NAFLD.
Abstract: Ultrasound imaging has been used for diagnosing lesions in the human body. In the process of acquiring ultrasound images, speckle noise may occur, affecting image quality and auto-lesion classification. Despite the efforts to resolve this, conventional algorithms exhibit poor speckle noise removal and edge preservation performance. Accordingly, in this study, a novel algorithm is proposed based on speckle reducing anisotropic diffusion (SRAD) and a Bayes threshold in the wavelet domain. In this algorithm, SRAD is employed as a preprocessing filter, and the Bayes threshold is used to remove the residual noise in the resulting image. Compared to the conventional filtering…techniques, experimental results showed that the proposed algorithm exhibited superior performance in terms of peak signal-to-noise ratio (average = 28.61 dB) and structural similarity (average = 0.778).
Abstract: OBJECTIVE: To explore the difference of 18F-FDG PET/CT images between the symptomatic and asymptomatic pulmonary tuberculosis, as well as the correlation between the standard uptake value (SUV) and the symptomatic/asymptomatic pulmonary tuberculosis. METHODS: A study dataset of 57 pulmonary tuberculosis cases was retrospectively assembled and analyzed. Among these cases, 30 were diagnosed having symptomatic pulmonary tuberculosis and 27 were asymptomatic pulmonary tuberculosis. PET/CT was performed in all 57 cases. The clinical data, CT images and PET/CT radioactive uptake data were analyzed using statistical data analysis software. RESULTS: All 57 cases showed radioactively high uptake, with the…maximum standard uptake value (SUVmax) of the lesion ranging from 1.60 to 27.30 and a mean value of 6.63±4.82. The symptomatic cases had an SUVmax of 8.76±4.97 and the asymptomatic cases had an SUVmax of 4.27±3.39. The SUVmax as well as singular or multiple lesions showed statistical differences between symptomatic and asymptomatic cases. CONCLUSION: The symptomatic pulmonary tuberculosis cases show significantly higher SUVmax than the asymptomatic cases. Based on the criteria of SUVmax greater than 2.0 to define active lesions, 100% of symptomatic cases might have active lesions while 70.4% of asymptomatic cases might have active lesions. Therefore, focused attention should be clinically paid on the asymptomatic cases of pulmonary tuberculosis to avoid miss diagnosis and delayed treatment.
Abstract: BACKGROUND: Intraoperative computed tomography (iCT) system has been developed focusing on combining the advanced imaging techniques for the best imaging modality. However, the use of iCT system in the operating rooms is limited due to the lack of flexible mobility. OBJECTIVE: This study aims to develop a mobile iCT imaging system and assess its imaging performance in a phantom study. METHODS: The mobile iCT system with mecanum omni-directional wheels has three major components namely, a rotating gantry, a slip-ring and a stationary gantry. Performance of mecanum iCT system was evaluated using the indices of signal-to-noise (SNR),…contrast-to noise (CNR), and spatial resolution (MTF). Anatomical landmarks on phantom images were assessed using a 5-point scale (5 = definitely seen; 4 = probably seen; 3 = equivocal; 2 = probably not seen; and 1 = definitely not seen). RESULTS: The mecanum iCT system can be conveniently used for a whole-body scan under intraoperative conditions even in narrow operating rooms due to a smaller turning radius. The image quality of the mecanum iCT system was found to be acceptable for clinical applications (with SNR = 162.72, CNR = 134.29 and MTF = 694 μm). The diagnostic scores on the phantom images were ‘definitely seen’ value. CONCLUSIONS: The proposed mecanum iCT system achieved the improved flexible mobility and has potential to better serve as a useful imaging tool in the clinical intraoperative setting.
Abstract: BACKGROUND: X-ray computed tomography (CT) can non-destructively examine objects by producing three-dimensional images of their internal structure. Although the availability of biomedical micro-CT offers the increased access to scanners, CT images of dense objects are susceptible to artifacts particularly due to beam hardening. OBJECTIVE: This study proposes and evaluates a simple semi-empirical correction method for beam hardening and scatter that can be applied to biomedical scanners. METHODS: Novel calibration phantoms of varying diameters were designed and built from aluminum and poly[methyl-methacrylate]. They were imaged using two biomedical micro-CT scanners. Absorbance measurements made through different phantom sections…were fit to polynomial and inversely exponential functions and used to determine linearization parameters. Corrections based on the linearization equations were applied to the projection data before reconstruction. RESULTS: Correction for beam hardening was achieved when applying both scanners with the correction methods to all test objects. Among them, applying polynomial correction method based on the aluminum phantom provided the best improvement. Correction of sample data demonstrated a high agreement of percent-volume composition of dense metallic inclusions between using the Bassikounou meteorite from the micro-CT images (13.7%) and previously published results using the petrographic thin sections (14.6% 8% metal and 6.6% troilite). CONCLUSIONS: Semi-empirical linearization of X-ray projection data with custom calibration phantoms allows accurate measurements to be obtained on the radiodense samples after applying the proposed correction method on biomedical micro-CT images.