Journal of X-Ray Science and Technology - Volume Pre-press, issue Pre-press
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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: We evaluate the impact of denoising and Metal Artefact Reduction (MAR) on 3D object segmentation and classification in low-resolution, cluttered dual-energy Computed Tomography (CT). To this end, we present a novel 3D materials-based segmentation technique based on the Dual-Energy Index (DEI) to automatically generate subvolumes for classification. Subvolume classification is performed using an extension of Extremely Randomised Clustering (ERC) forest codebooks, constructed using dense feature-point sampling and multiscale Density Histogram (DH) descriptors. Within this experimental framework, we evaluate the impact on classification accuracy and computational expense of pre-processing by intensity thresholding, Non-Local Means (NLM) filtering, Linear Interpolation-based MAR (LIMar) and…Distance-Driven MAR (DDMar) in the domain of 3D baggage security screening. We demonstrate that basic NLM filtering, although removing fewer artefacts, produces state-of-the-art classification results comparable to the more complex DDMar but at a significant reduction in computational cost - bringing into question the importance (in terms of automated CT analysis) of computationally expensive artefact reduction techniques. Overall, it was found that the use of MAR pre-processing approaches produced only a marginal improvement in classification performance (< 1%) at considerable additional computational cost (> 10×) when compared to NLM pre-processing.
Abstract: OBJECTIVE: To explore the clinical efficacy and safety of percutaneous transvenous retrieval of intravascular fractured catheter and to evaluate the possible reasons and final results in cancer patients. METHODS: A dataset of 19 patients was used. Percutaneous transvenous retrieval of intravascular fractured catheter was performed in each patients. Clinical data was retrospectively analyzed with respect to the efficacy, safety and outcome, and chest radiography was performed to verify that no catheter fragments were left. RESULTS: Two cases had peripherally inserted central catheter and 17 had subcutaneous implanted port catheter. The catheter fragments were…located in the brachiocephalic vein-superior vena cava (n = 1), superior vena cava (n = 1), superior and inferior vena cava (n = 1), superior vena cava-right atrium (n = 2), brachiocephalic vein-superior vena cava-right atrium (n = 1), superior vena cava-right atrium-right ventricle (n = 6), brachiocephalic vein-superior vena cava-right atrium and right ventricle (n = 1) and pulmonary artery (n = 6), respectively. All of these catheter fragments were retrieved successfully. No complications such as bleeding and thrombosis were found. CONCLUSION: Percutaneous transvenous retrieval is a safe, minimally invasive and relatively simple procedure for the patients with fractured catheter and should be recommended as the first choice.
Abstract: BACKGROUND: High dose efficiency of photon counting detector based spectral CT (PCD-SCT) and its value in some clinical diagnosis have been well acknowledged. However, it has not been widely adopted in practical use for medical diagnosis and security inspection. OBJECTIVE: To evaluate the influence on PCD-SCT from multiple aspects including the number of energy channels, k-edge materials, energy thresholding, basis functions in spectral information decomposition, and the combined optimal setting for these parameters and configurations. METHODS: Basis material decomposition after spatial reconstruction is applied for PCD-SCT. A “one-step” synthesis method, merging decomposition with synthesis, is proposed…to obtain virtual monochromatic images. An I-RMSE is computed using the bias part of I-RMSE to describe the difference of a synthesized signal from ground truth and the standard deviation part of I-RMSE to express the noise level. In addition, virtual monochromatic images commonly used in the medical area are also synthesized. Both numerical simulations and practical experiments are conducted for validation. RESULTS: Results indicated that the I-RMSE for matters significantly reduced with an increased number of energy channels compared with dual-energy channel. The maximum reduction is 6% for triple-, 18% for quadruple-and 24% for quintuple-energy, respectively. However, the improvement is not linear, and also slows down after the number of energy channels reaches a certain number. Contrast agents of high concentration can introduce up to 50% error to surrounding matters. Moreover, different energy partitions influence the total error, which demonstrates the necessity of energy threshold optimization. Last, the optimal basis-material combination varies according to targeted imaging matters and the interested monochromatic energies. CONCLUSIONS: Gain from more energy channels could be significant with the increase of energy channel number. Introduction of contrast agents in scanned objects will increase overall error in spectral CT imaging. Energy thresholding optimization is beneficial for information recovery. Moreover, the choice of basis materials could also be important to obtain low noise results. With these studies of the effect from various configurations for PCD-SCT, one may optimize the configuration of PCD-SCT accordingly.
Abstract: BACKGROUND: Low-quality medical images may influence the accuracy of the machine learning process. OBJECTIVE: This study was undertaken to compare accuracy of medical image classification among machine learning methods, as classification is a basic aspect of clinical image inspection. METHODS: Three types of machine learning methods were used, which include Support Vector Machine (SVM), Artificial Neural Network (ANN), and Convolution Neural Network (CNN). To investigate changes in accuracy related to image quality, we constructed a single dataset using two different file formats of DICOM (Digital Imaging and Communications in Medicine) and JPEG (Joint Photographic Experts Group).…RESULTS: The JPEG format contains less color information and data capacity than the DICOM format. CNN classification was accurate for both datasets, whereas SVM and ANN accuracy decreased with the loss of data from DICOM to JPEG formats. CONCLUSIONS: CNN is more accurate than conventional machine learning methods that utilize the manual feature extraction.
Abstract: OBJECTIVE: Correlation between myocardial infarction (MI) scar by cardiac magnetic resonance and the Lown’s classification of ventricular premature beats (VPBs) is poorly understood. This study aims to investigate the correlation between the MI scar characteristics by delayed-enhancement magnetic resonance imaging (DE-MRI) and the Lown’s classification of VPBs. METHODS: Sixty-five patients, in the convalescence stage and consolidation phase of MI, were included in this retrospective study. All patient were divided into VPBs group (n = 39) and non-VPBs group (n = 26 patients) according to the clinical diagnostic criteria of Universal Definition of MI scar. VPBs patients were assigned to Lown’s…I-II group and Lown’s III-IV subgroup in accordance with the Lown classification criteria. Cardiac function parameters and MI scar characteristics were detected by cardiac magnetic resonance (CMR) and DE-MRI, respectively. RESULTS: Lown’s classification was negatively correlated with left ventricular ejection fraction (LVEF), peak ejection rate (PER) and peak filling rate (PFR) (– 0.724, – 0.628, – 0.559), and positively correlated with MI area, MI integral, MI segments number and left ventricular end systolic volume (LVESV) (0.673, 0.655, 0.586, and 0.514), respectively. CONCLUSIONS The study indicated that MI area and MI integral were strongly associated with Lown’s classification.
Abstract: BACKGROUND: Anesthesia may alter the cellular components contributing to the magnetic resonance imaging (MRI) signal intensities. Developing awake animal models to evaluate cerebral function has grown in importance. OBJECTIVE: To investigate a noninvasive strategy for dynamic MRI (dMRI) of awake rabbits during carbogen challenge. METHODS: A nonmetallic assistive device with a self-adhering wrap secure procedure was developed for the head fixation of awake rabbits. Multi-shot gradient echo echo-planar imaging sequence was applied for the dMRI on a 1.5 T clinical MRI scanner with a quadrature head coil. The carbogen challenge pattern was applied in…a sequence of air - carbogen - air - carbogen - air. Twelve scans were performed for each block of carbogen challenge. T2 -weighted fast-spin echo and T1 -weighted gradient echo sequences were performed before and after dMRI to evaluate the head position shifts. The whole dMRI scan time was about 30 minutes. RESULTS: The position shift of 8 rabbits in the x-and y-direction was less than 3%. The average MRI signal intensities (SI) from the 8 rabbits during carbogen challenge was fitted well using exponential growth and decay functions. The average MRI SI increase due to carbogen inhaling was 1.51%. CONCLUSIONS: The proposed strategy for head dMRI on an awake rabbit during carbogen challenge is feasible.
Abstract: PURPOSE: To explore the hemodynamic characteristics of variously differentiated breast ductal carcinoma (BDC) using the dynamic contrast-enhanced CT (DCE-CT) based CT perfusion imaging (CTPI), including the specific perfusion parameter values, and to identify potential clinical applications in the cell differentiation degree of BDC. MATERIALS AND METHODS: Forty patients with breast ductal carcinoma confirmed by needle puncture biopsy were studied prospectively using CTPI on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using a tumor perfusion protocol in the CT perfusion software package to measure 4 parameters namely, blood flow…(BF), blood volume (BV), mean transit time (MTT), and the permeability surface (PS) area product. The different differentiated BDC with CT perfusion parameters were divided into 3 groups of high, moderate and poor differentiation. The comparison among these groups were then made using statistical data analysis software. RESULTS: The patients were categorized into three groups of 12, 13, and 15 highly, moderately and poorly differentiated ductal carcinoma cases, respectively. Comparing the perfusion parameters values of the three groups, BF, BV, and PS values increased from highly to poorly differentiated BDC cases. Differences between the highly and moderately or poorly differentiated groups were all statistically significant for BF, BV, and PS values (p < 0.05), while MTT value showed no statistical difference among the three groups (p > 0.05). CONCLUSION: CTPI is a functional imaging technology from the perspective of hemodynamics with potential clinical applications. Three parameters of BF, BV and PS values have potential to serve as indicators of the cell differentiation degree of the breast ductal carcinoma.
Keywords: Breast cancer, tumor differentiation, dynamic contrast-enhanced CT, cancer prognosis
Abstract: Influence of x-ray pulse generated from gamma spectrometers should be eliminated in applications, which typically uses pulse shape techniques between gamma and x-ray pulses. In this study, we proposed and tested several algorithms aiming to eliminate this influence. The algorithms are based on curve fitting (CF), artificial neural network (ANN), system identification, peak shape, amplitude search with curve fitting and pulse tracking methods. Gamma pulses and X-ray pulses are detected by NaI(TI) scintillator detector and Silicon lithium Si(Li) detector, respectively. The developed algorithms are tested using 32,000 total instantaneous detector events of acquired gamma pulses and 65,536 total instantaneous detector…events of x-ray source. An algorithm using the least square curve fitting method is applied for differentiation between gamma and x-ray pulses. ANN is employed as a classifier for identification of extracted spectrum and Bispectrum features of gamma and x-ray pulses. A comparison between identification results due to extracted spectrum and Bispectrum features is established. System identification algorithm is then built to determine the detection system response of each radiation pulse, which includes various models to attain best fitting. These models are Auto-regressive model with external input (ARX), the linear parametric model (IV) and process models (P1D). The peak shape algorithm is also tried, which depends on the individual classification of pulse width. The amplitude search with curve fitting algorithm is implemented. Moreover, the pulse tracking algorithm is investigated for PSD between gamma and x-ray pulses. The maximum peak of contaminated pulse is tracked using a suggested peak search method. Then, pulse position is estimated using matrix method. Comparison between these algorithms is conducted based on the evaluation of light of residuals, fitting error and processing time. The results confirm that peak shape algorithm is the best one from computational speed point of view, while ANN algorithm using Bispectrum feature extraction method is the most appropriate one that yields 100% accuracy over noisy environment with longer processing time. In addition, the system identification algorithm is the optimal algorithm that achieves zero fitting error under clean environment. These proposed algorithms for PSD between gamma and x-ray pulses lead to design efficient spectrometers with optimal applicability in various environments.
Keywords: Spectrometers, medical imaging, FPGA, digital signal processing
Abstract: Inspired by the compressed sensing (CS) theory, introducing priori information of sparse image into sparse-view reconstruction algorithm of computed tomography (CT) can improve image quality. In recent years, as a special case of CS, total variation (TV) reconstruction algorithm that uses prior information of both image sparsity and edge direction has attracted much research interest in sparse-view image reconstruction due to its ability to preserve image edges. In this paper, we propose a new adaptive-weight total variation (NAWTV) algorithm for CT image reconstruction, which is derived by considering local gradient direction continuity and the anisotropic edge property. The anisotropic edge…property is used to consolidate the image sparsity, where the associated weights are expressed as a combination of exponential and cosine function. The weights can also be adjusted adaptively according the local image intensity gradient. The NAWTV algorithm is numerically implemented with gradient descent method. The typical Shepp-Logan phantom and FORBILD head phantom are employed to perform image reconstruction simulation. To evaluate performance of NAWTV algorithm, we compared it with TV and AwTV reconstruction algorithms in experiments. Numerical experimental results verified the effectiveness and feasibility of the proposed algorithm. Comparison results also showed that the NAWTV algorithm achieved a satisfactory performance in suppressing artifacts and preserving the edge structure details information of the reconstructed image.
Keywords: Compressed sensing, computed tomography, sparse-view reconstruction, total variation
Abstract: In this study, soft X-ray spectromicroscopy was applied to investigate and analyze the distribution of DNA and RNA in a mammalian cell at the spatial resolution of 400 nm. The relative distribution of DNA and RNA was examined by the SVD (singular value decomposition) method in aXis2000 program using combined full spectra of DNA and RNA at the absorption edge regions of carbon, nitrogen and oxygen. The absorption of nucleic acid was evaluated using 1s-π * transitions in the NEXAFS spectra at the nitrogen K absorption edge and distributed to DNA and RNA according to the relative level obtained above. The…study results revealed the usefulness of the SVD method to discriminate closely related molecules such as DNA and RNA.
Keywords: STXM, DNA and RNA mapping, quantitative study, cultured mammalian cell