Radiation Images Research Articles

Effect of Instrument Navigation on C-arm Radiation and Time during Spinal Procedures: A Clinical Evaluation.

As minimally invasive spine surgery gains popularity, a focused effort must be made to reduce intraoperative radiation exposure to levels as low as reasonably achievable. Here, we demonstrate the clinical efficacy of a novel technology to aid in instrument navigation that aims to reduce intraoperative radiation exposure, number of fluoroscopic images, and time required to perform the most radiation intensive portions of a multitude of spinal procedures. An internally randomized controlled study was performed over a 1-month period in order to clinically evaluate the effect of the C-arm assisted instrument tracking system, TrackX, on surgeon workflow, time, and radiation emitted. Three surgeons performed multiple spinal procedures on a total of 10 study patients and an additional 3 control patients. The surgeries encompassed minimally invasive spinal techniques and spanned extreme lateral interbody fusion, oblique lumbar interbody fusion, transforaminal lumbar interbody fusion along with percutaneous iliac screw placement, hardware removal, and kyphoplasty. The tasks studied included skin marking, first dilator insertion, localization for hardware placement and hardware removal. Overall radiation reduction was 83% (P < .0001). Overall reduction in x-rays taken was 78% (P < .0001). Overall time reduction was 81% (P = .0003). Statistical significance held for each surgeon studied and for nearly every procedure type. In these 10 study procedures, over 2 hours of overall operating room time was saved, all while requiring negligible set up time and no system calibration or supplementary x-rays to be taken. There were no adverse outcomes for any study patient, and there was no case where TrackX was not able to successfully complete a given portion of a procedure. TrackX instrument navigation is a clinically efficacious and accurate instrument tracking modality. This is the first instrument navigational technology that reduces radiation exposure and images required to complete a procedure while decreasing operative time. TrackX thus allows increased surgical efficiency while increasing operative efficiency and improving intraoperative safety. 2.

Method for Determining the Measurement Uncertainty of the Detailing Coefficients of the Wavelet Transform of Image Brightness Profiles

This study analyzed the relevance of using measurement methods based on visual data and identified the main problems that arise when calculating the measurement uncertainty of the estimates of quantitative characteristics of images in automated image analysis systems due to the lack of general recommendations for this type of calculation. Moreover, the study highlights the challenges in developing a method for calculating the measurement uncertainty of the detailing coefficients of the wavelet transform applied to the automated analysis of gas-discharge radiation images of water. To evaluate the biological properties of water and highlight the corresponding informative features of the gas-discharge radiation images, a one-dimensional wavelet transform of the brightness profile is proposed. This method of calculating the uncertainty is based on the results of repeated cases and helps reveal the measurement uncertainty of the quantitative characteristics of the images.

NIPC-based uncertainty analysis of infrared radiation from rocket exhaust plumes caused by nozzle exit conditions

In this study, an uncertainty analysis for the infrared radiation characteristics of rocket exhaust plumes at representative trajectory points is performed. Owing to the instability of the rocket motor’s working characteristics, numerical rocket plume infrared radiation predictions possess significant uncertainties. In this study, four epistemic uncertain variables (freestream velocity, nozzle exit pressure, temperature, and velocity) are considered for uncertainty and sensitivity analyses. Based on the infrared signature analysis tool, the response surface of statistical samples is established through the point collocation nonintrusive polynomial chaos expansion method. Polynomial chaos expansion coefficients are solved using the quadrature method to calculate the statistical characteristics and uncertainty of random input variables. The tensor-product quadrature sparse grid method is utilized to reduce the number of samples for multiple input variables. Based on these models, the uncertainty quantification of infrared radiation for Atlas-IIA rocket plumes is analyzed, including the flows, radiation images, spectra, and radiance. The results show that the uncertainty mainly results from afterburning at low altitude, and the nozzle exit velocity has a significant influence on the radiation intensity of the plume. With an increase in altitude, the uncertainty of infrared radiation owing to the afterburning effect decreases, and the influence of the freestream velocity increases. In addition, the proportion of radiation intensity in the 4.3-μm band is higher than that in the 2.7-μm band, and the corresponding uncertainty band is gradually widened. The nozzle exit temperature is the dominant factor that affects the radiation characteristics of the plume at high altitudes. These results of uncertainty and sensitivity analyses are helpful for improving numerical models of the plume infrared signature.

Image reconstruction using multi-energy system matrices with a scintillator-based gamma camera for nuclear security applications

The system response of a gamma camera is dependent on the photon energy, thus the energy-dependent response function needs to be considered to improve the quality and fidelity of reconstructed images for identifying radionuclides in security applications. In this study, two reconstruction strategies using the maximum-likelihood expectation maximization (MLEM) algorithm with the multi-energy system matrices calculated by Monte Carlo simulations are proposed. The difference between the two is in data acquisition; one uses the sum of all events into a single projection image while the other sorts them into separate energy windows. Various radiation images of gamma-ray sources were simulated with a Monte Carlo code, and an actual image was acquired with a gamma camera. Both simulation and experiment results demonstrated the feasibility of the presented multi-energy reconstruction strategies in the detection of orphan sources.

ПОВЫШЕНИЕ РАЗРЕШАЮЩЕЙ СПОСОБНОСТИ СЛАБОКОНТРАСТНЫХ ИЗОБРАЖЕНИЙ В ПРОСТРАНСТВЕ ФАЗОВЫХ ХАРАКТЕРИСТИК СИНГУЛЯРНОГО РАЗЛОЖЕНИЯ

Рассмотрены информационные возможности фазовых характеристик, синтезируемых на основе метода сингулярного разложения применительно к решению задач сегментации при визуальном анализе слабоконтрастных изображений. Показано, что переход в новое пространство признаков, полученных на основе параметров ортогонального преобразования, обеспечивает повышение чувствительности и разрешаюшей способности при выявлении объектов интереса (аномальных областей). Приведены экспериментальные результаты на примере реальных изображениях.

Temperature Measurement Method of Flame Image Fusion with Different Exposures

Fixed exposure will lead to underexposure or overexposure of collected flame radiation images using CCD, which has a great influence on the temperature measuring accuracy. A temperature measurement method was proposed by image fusion with multi-exposure, which can eliminate the influence of insufficient underexposure and overexposure. The approach was first to acquire a group of flame radiation images during different exposures. Then a partial region with good exposure effect in each radiation image was obtained by segmentation, with which the complete flame image can be spliced together. An experimental system was built to calibrate the temperature measurement parameters by two-color pyrometry through a blackbody furnace. The relation between exposure time and monochromatic gray level, as well as the relation between the temperature and temperature measurement coefficient were obtained. A candle flame was selected as the measuring object and the complete and accurate flame temperature distribution was acquired following our proposed method. The experimental results show that, compared with the temperature measurement using a single exposure time, our method can effectively avoid the measurement error caused by underexposure and overexposure, and improve the measurement accuracy.

Ignition and Combustion Behavior of Sintered‐B/MgB2 Combined with KNO3

AbstractTo further enhance the performance of B/KNO3 (BPN) igniter, sintered B/MgB2 (s‐B/MgB2) powder was proposed to be used as a boron substitute. The amount of heat release was tested by oxygen bomb and thermogravimetry/differential scanning calorimetry (TG/DSC). s‐B/MgB2/KNO3 (sBPN) igniter could not release as much heat as BPN igniter in the oxygen bomb due to the reduced calorific value of the s‐B/MgB2. However, calculations show that s‐B/MgB2 reached an over 90 % heat release efficiency in oxygen bomb, compared to that of 53.34 % for boron. At heating rate of 10 K min−1 in TG/DSC experiment, 19.5 % sBPN (sBPN with 19.5 wt. % s‐B/MgB2 powder) has a heat release of 1815 J g−1 and experienced an exothermic span of 2.10 min, whereas it took 24.5 % BPN (BPN with 24.5 wt. % boron powder) 3.45 min to release 1465 J g−1. The pressure‐time curve (P‐t curve), burning rate and combustion temperature were determined. The P‐t curve indicates that the combustion pressure was more readily established with the sBPN than with the BPN. The maximum pressure rise of sBPN was 362.0 Pa ms−1, whereas the figure for BPN is 77.2 Pa ms−1. Coupled with infrared radiation (IR) temperature thermometer, the distribution of the flame temperature field during combustion was obtained. It is shown that the combustion temperature of 19.5 % sBPN igniter is approximately 800 K higher than that of 24.5 % BPN. IR images of the combustion process show that the temperature difference of the 19.5 % sBPN flame is smaller than that of the 24.5 % BPN. 19.5 % sBPN also produces more hot residue, which contains KMgF3, resulting in a longer high‐temperature duration. The higher combustion pressure and temperature and more residue may enable the sBPN to readily ignite the following charge.

Remote detection of radioactive hotspot using a Compton camera mounted on a moving multi-copter drone above a contaminated area in Fukushima

ABSTRACTThe Fukushima Daiichi Nuclear Power Station (FDNPS), operated by Tokyo Electric Power Company Holdings, Inc., suffered a meltdown as a result of a large tsunami triggered by the Great East Japan Earthquake on 11 March 2011. To proceed with environmental recovery, a radiation distribution map that indicates the distribution of radioactive substances is extremely important to establish detailed decontamination plans. We developed a remote radiation imaging system comprising a lightweight Compton camera mounted on a multi-copter drone to measure the distribution of radioactive substances remotely. The proposed system can perform radiation imaging using the Compton camera while flying and moving. In addition, the distribution of radioactive substances can be visualized three-dimensionally by drawing the radiation images captured by the Compton camera on a three-dimensional (3D) topography model acquired by a 3D-LiDAR (Light Detection and Ranging) system. We conducted a survey of radioactive hotspots in difficult-to-return zones in the coastal area of Fukushima, Japan. The drone system realized 3D visualization of several hotspots. Such remote technology would be useful for monitoring the difficult-to-return zone as well as for monitoring the distribution of radioactive substances inside the FDNPS site where decommissioning work is ongoing.

More than meets the eye: Longitudinal visual system neurodevelopment in very preterm children and anophthalmia

Anophthalmia, characterized by the absence of an eye(s), is a rare major birth defect with a relatively unexplored neuroanatomy. Longitudinal comparison of white matter development in an anophthalmic (AC) very preterm (VPT) child with both binocular VPT and full-term (FT) children provides unique insights into early neurodevelopment of the visual system. VPT-born neonates (<32wks gestational age), including the infant with unilateral anophthalmia, underwent neuroimaging every two years from birth until 8 years. DTI images (N = 168) of the optic radiation (OR) and a control track, the posterior limb of the internal capsule (PLIC), were analysed. The diameter of the optic nerves (ON) were analysed using T1-weighted images. Significant group differences in FA and AD were found bilaterally in the OR and PLIC. This extends the literature on altered white matter development in VPT children, being the first longitudinal study showing stable group differences across the 4, 6 and 8 year timepoints. AC showed greater deficits in FA and AD bilaterally, but recovered towards VPT group means from 4 to 8 years-of-age. Complete lack of binocular input would be responsible for these early deficits; compensatory mechanisms may facilitate structural improvement over time. AC’s ON exhibited significant atrophy ipsilateral to the anophthalmic eye. Functionally, AC displayed normal visual acuity and form perception, but naso-temporal bias in motion perception. Following these groups and AC longitudinally enabled novel understanding of the joint influence of monocular vision and VPT birth on neurodevelopment.

Method calculating of uncertainty in evaluating the detailing coeffi cients of wavelet-conversion of profi le brightness image

The analysis of the relevance of the use of measurement methods based on obtaining visual data. The main problems that arise in automated image analysis systems in calculating the uncertainty of estimates of quantitative characteristics of images are identifi ed. Since modern methods of collecting and transforming visual data are characterized by great diversity, at the moment there are no general recommendations for calculating the uncertainty of estimates of their geometric and brightness parameters. The article is devoted to the development of a method for calculating uncertainty in evaluating the detailed coeffi cients of the wavelet transform, which is used in the automated analysis of images of gas-discharge radiation of water. The method based on recording gas-discharge radiation of water samples in an external pulsed electromagnetic fi eld was chosen to study the biological properties of water, since the formation of a gas discharge in the air gap between conductors directly depends on the presence of free charge carriers that can be simulated from the surface of the object under study. The number of free charge carriers determines the biological properties of water, since they affect the ability of drinking water to provide metabolic processes in living organisms by maintaining the normal course of redox reactions at the cellular level. To assess the biological properties of water and highlight the corresponding informative features of gas-discharge images, it is proposed to use the method of one-dimensional wavelet transform of the brightness profi le. A method for calculating the uncertainty in evaluating the detailed coeffi cients of the wavelet transform is considered. The proposed method for calculating the uncertainty is based on the results of repeated observations and allows us to estimate the uncertainty of the measurement results presented in the form of quantitative signs of images.

Integrated assessment of the state of sewage mine waters based on gas-discharge radiation method

The existing environmental problems resulting from the use and subsequent discharge of water by mining and metallurgical enterprises are analyzed. The relevance of developing methods for an integrated assessment of water properties is presented, which will allow the study of not only physical-chemical, but also the biological parameters of water. Experimental studies of water samples are conducted based on the method of gas-discharge radiation. The existing methods for extracting informative features of gas-discharge radiation images of liquid-phase objects are analyzed. Histograms of gas-discharge radiation images of various types of water were constructed and studied. The expediency of dividing images into separate fragments, characterized by common texture features, is shown. The analysis of texture features is carried out based on the use of the Fourier transform. Using the Fourier transform for the corresponding luminance vectors, the spectra have been obtained of the spatial distribution of the frequencies of brightness changes, which are used as texture features to identify the specific characteristics of the gas-discharge tracks formation. It has been determined that the developed method of water analysis allows assessing its biological properties, which is based on the values of the spatial frequency range. The advantage of the proposed method over the existing ones is the possibility of quantitative assessment in the form of numerical values of the covered range of spatial frequencies. The proposed method of studying the biological properties of water can be used as part of modern environmental monitoring systems.

The estimation of the laser point temperature based on CNN (Convolutional Neural Network)

For the requirements of the laser temperature in additive manufacturing, there is a high precision and high heat need in the industry. The method is proposed to estimate the temperature of laser point, which is based on CNN. In this method, a model of CNN is carried out. The collected laser thermal radiation images are used to train the model. Image recognition and isotherm estimation can be obtained by the trained model. The conclusion can be verified by the experiment. The isotherm and temperature of the laser can be measured efficiently in this method.

The role of artificial intelligence in medical imaging research.

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging research, both in diagnostic and therapeutic. For diagnostic imaging alone, the number of publications on AI has increased from about 100–150 per year in 2007–2008 to 1000–1100 per year in 2017–2018. Researchers have applied AI to automatically recognizing complex patterns in imaging data and providing quantitative assessments of radiographic characteristics. In radiation oncology, AI has been applied on different image modalities that are used at different stages of the treatment. i.e. tumor delineation and treatment assessment. Radiomics, the extraction of a large number of image features from radiation images with a high-throughput approach, is one of the most popular research topics today in medical imaging research. AI is the essential boosting power of processing massive number of medical images and therefore uncovers disease characteristics that fail to be appreciated by the naked eyes. The objectives of this paper are to review the history of AI in medical imaging research, the current role, the challenges need to be resolved before AI can be adopted widely in the clinic, and the potential future.

Use of a Method for Contour Analysis of Radiation Images of Malignant Breast Tumors on the Basis of Retrospective Material

Objective. To enhance the reliability of visual analysis of X-ray mammograms, by applying the mathematical models of neoplasms and a method for their processing based on the mathematical apparatus of contour analysis.Material and methods. Two data sets were generated from X-ray mammograms obtained from 38–82 year old patients at routine examinations in the Republican Oncology Dispensary. The first set contained 100 packages of X-ray mammographic images that failed to reveal abnormal malignant changes. The second set was represented by 168 packages of X-ray mammographic images showing morphologically verified breast cancer. All the packages of mammographic images are presented in the standard direct craniocaudal and mediolateral oblique projections. The images were obtained using an analog mammograph. Digital copies of images having a resolution of 600 dpi were obtained for subsequent computer processing. The latter of digital mammographic images involved segmentation of space-occupying lesions, determination of the linearity factor of their outlines, and differential diagnosis of space-occupying lesions based on the calculated value of the linearity factor of their outlines.Results. An algorithm was elaborated for identifying the outlines of space-occupying lesions on X-ray mammographic images. The sequence of complex-valued vectors approximating its curve was used as a mathematical model of the outline. The concept on the outline linearity factor, which quantitatively characterizes its shape, was introduced. A method was developed for the objective classification of malignant and benign space-occupying lesions based on the value of the introduced linearity factor. The outlines of benign space-occupying lesions in the breast were ascertained to be characterized by the higher linearity factor (in the region of 0.3–0.4) (BI-RADS category 2), while the outlines of malignant tumors had a much lower value of this factor (in the order of 0.05–0.1) (BI-RADS categories 4–5). The main quantitative measures (sensitivity, specificity, and accuracy) of the informative value of the proposed method were determined. The latter was shown to have a higher specificity than the traditional visual analysis carried out by a radiologist. This allows the proposed method to be used as an additional procedure in the visual analysis of mammograms to enhance the reliability of clinical findings.Conclusion. The practical value of the method is in quantitatively evaluating the shapes of malignant breast neoplasms, in reducing the performance of a mammographic examination, and in increasing its objectivity. The proposed method makes it possible to reduce the time of analyzing X-ray mammograms and to enhance the reliability of clinical findings.

An Identity Authentication Method Combining Liveness Detection and Face Recognition.

In this study, an advanced Kinect sensor was adopted to acquire infrared radiation (IR) images for liveness detection. The proposed liveness detection method based on infrared radiation (IR) images can deal with face spoofs. Face pictures were acquired by a Kinect camera and converted into IR images. Feature extraction and classification were carried out by a deep neural network to distinguish between real individuals and face spoofs. IR images collected by the Kinect camera have depth information. Therefore, the IR pixels from live images have an evident hierarchical structure, while those from photos or videos have no evident hierarchical feature. Accordingly, two types of IR images were learned through the deep network to realize the identification of whether images were from live individuals. In comparison with other liveness detection cross-databases, our recognition accuracy was 99.8% and better than other algorithms. FaceNet is a face recognition model, and it is robust to occlusion, blur, illumination, and steering. We combined the liveness detection and FaceNet model for identity authentication. For improving the application of the authentication approach, we proposed two improved ways to run the FaceNet model. Experimental results showed that the combination of the proposed liveness detection and improved face recognition had a good recognition effect and can be used for identity authentication.

Predicting the Observational Signature of Migrating Neptune-sized Planets in Low-viscosity Disks

Abstract The migration of planetary cores embedded in a protoplanetary disk is an important mechanism within planet-formation theory, relevant for the architecture of planetary systems. Consequently, planet migration is actively discussed, yet often results of independent theoretical or numerical studies are unconstrained due to the lack of observational diagnostics designed in light of planet migration. In this work we follow the idea of inferring the migration behavior of embedded planets by means of the characteristic radial structures that they imprint in the disk’s dust density distribution. We run hydrodynamical multifluid simulations of gas and several dust species in a locally isothermal α-disk in the low-viscosity regime (α = 10−5) and investigate the obtained dust structures. In this framework, a planet of roughly Neptune mass can create three (or more) rings in which dust accumulates. We find that the relative spacing of these rings depends on the planet’s migration speed and direction. By performing subsequent radiative transfer calculations and image synthesis we show that—always under the condition of a near-inviscid disk—different migration scenarios are, in principle, distinguishable by long-baseline, state-of-the-art Atacama Large Millimeter/submillimeter Array observations.

Investigating Detectability of Infrared Radiation Based on Image Evaluation for Engine Flame

Aiming at the application requirements of infrared detection, the influence of earth background interference on plume radiation detection is investigated and discussed in this article. The infrared image of the earth’s atmospheric background radiation is simulated by the spectral correlation based on the conversion model of the surface radiation with different bands. The infrared radiation image of the jet flame and the background is generated by overlapping the infrared radiation of the engine flame and the background radiation according to the detection angle of view. Through the image quality evaluation model, the detectability of the flame is analyzed. The simulating results show that the comprehensive statistical features such as image information entropy, variance and signal-to-clutter ratio can be used to evaluate the detectability of the engine flame.

Prediction Model of Alcohol Intoxication from Facial Temperature Dynamics Based on K-Means Clustering Driven by Evolutionary Computing

Alcohol intoxication is a significant phenomenon, affecting many social areas, including work procedures or car driving. Alcohol causes certain side effects including changing the facial thermal distribution, which may enable the contactless identification and classification of alcohol-intoxicated people. We adopted a multiregional segmentation procedure to identify and classify symmetrical facial features, which reliably reflects the facial-temperature variations while subjects are drinking alcohol. Such a model can objectively track alcohol intoxication in the form of a facial temperature map. In our paper, we propose the segmentation model based on the clustering algorithm, which is driven by the modified version of the Artificial Bee Colony (ABC) evolutionary optimization with the goal of facial temperature features extraction from the IR (infrared radiation) images. This model allows for a definition of symmetric clusters, identifying facial temperature structures corresponding with intoxication. The ABC algorithm serves as an optimization process for an optimal cluster’s distribution to the clustering method the best approximate individual areas linked with gradual alcohol intoxication. In our analysis, we analyzed a set of twenty volunteers, who had IR images taken to reflect the process of alcohol intoxication. The proposed method was represented by multiregional segmentation, allowing for classification of the individual spatial temperature areas into segmentation classes. The proposed method, besides single IR image modelling, allows for dynamical tracking of the alcohol-temperature features within a process of intoxication, from the sober state up to the maximum observed intoxication level.

GPU Accelerated Stochastic Origin Ensemble Method With List-Mode Data for Compton Camera Imaging in Proton Therapy

Proton beam therapy has the advantages over other forms of radiation therapy because it does less damage to healthy tissue while treating cancerous tissue. These advantages arise from the high dose deposition at the end of the proton beam which is known as the Bragg peak. This paper proposes a new architecture for graphics processing unit (GPU)-accelerated stochastic origin ensemble (SOE) algorithm, eventually achieves a great acceleration and allows to reconstruct images of the gamma radiation produced by proton beam in real time. The object of this paper is to improve the run time of SOE algorithm for improving the accuracy of the proton therapy. In previous studies, it is difficult to reconstruct images of prompt gamma (PG) ray in real time in proton therapy. After analyzing the structure of the SOE algorithm, we correspond each gamma ray detected by Compton camera (CC) to each thread in GPU, initialize the origin cones in GPU, and use data structures which are suitable for parallelization, shared memory, and random number lists to speed up parallel program. To evaluate the proposed method, we use the parallel SOE algorithm to reconstruct the sources with the CC imaging system, which is simulated by Geant4. The parallel program on the GPU eventually achieves a 25× speedup over serial CPU run, reconstructing images of gamma radiation in 0.4 s. In the end, we also accelerate the Monte Carlo-based back projection (MC-BP) algorithm, the parallel program achieves a 79× speedup over serial CPU run.

Calculation and experimental verification of radiation characteristics of spontaneous chaff clouds in high-speed flows

When spontaneous chaffs diffuse in air, numerous radiations are shielded, absorbed, and reflected between chaffs, and there is interaction between the chaffs and the air. This makes it relatively complicated to calculate radiation transmission. To calculate the spatial distribution and generate radiation images of spontaneous chaffs, a radiation calculation model based on reverse path sampling was constructed which takes account of the transmission characteristics of radiation. This model hypothesizes that all detectors transmit light outward uniformly in the opposite direction of the radiation. After sampling statistics of light routes, the number and intensity of lights received by detectors along the radiation path were calculated. Next, a spontaneous combustion model of chaff was constructed. In this model, the effects of the porous structure of the chaff surface on the combustion rate of reactive metals are considered. The accuracy of this model was proved by comparing calculated results with experimental data. Finally, the spatial distribution of chaff clouds was calculated and their radiation images obtained. The results from the constructed model proved to be highly accurate when compared with measurement data from an experimental rocket sled.