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Abstract: Transmission sources used for image attenuation correction, allowing image quantification, are collimated to reduce scatter. We propose the same effect can be achieved for an uncollimated source by increasing source to patient distance. The aim was to compare planar image performance characteristics and absorbed doses of uncollimated and collimated radioactive printed paper transmission sources. The scatter contribution to the uncollimated 99mTc source data was evaluated for different combinations of detector phantom distance, detector source distance and phantom source distance. Measurements were performed by increasing the Lucite phantom thickness in 1cm steps to 20 cm. Spatial resolution, detection efficiency and entrance absorbed dose rate were measured for the uncollimated and collimated transmission source images. Results derived from the energy spectra, obtained with the uncollimated transmission source indicate that scatter contribution increases with decreasing detector source distance. The scatter component in the uncollimated transmission images (detector source distances≥60cm; phantom source distances≥40cm) was comparable to that obtained with collimated transmission images. Attenuation coefficients obtained compared well (0.168cm−1 vs. 0.171cm−1). The full widths at half maxima differed by less than 0.9mm. The detection efficiency of the uncollimated source was 2.5 times higher than obtained with the collimated source. The entrance absorbed dose obtained from an uncollimated source was 3.75 times larger than that obtained from the collimated source. An uncollimated transmission source (detector source distance≥60cm) results in acceptable image characteristics and presents a low cost, low dose, high efficiency option for transmission imaging. [ABSTRACT FROM AUTHOR]

Objectives: To develop and evaluate methods for assembling radiopaque printed paper sheets to realistic patient phantoms for CT dose and image quality testing.Methods: CT images of two patients were radiopaque printed with aqueous potassium iodide solution (0.6 g/ml) on paper. Two methods were developed for assembling the paper sheets to head and neck phantoms. (1) Printed sheets were fed to a paper-based 3D printer along with corresponding 3D printable STL files. (2) Paper stacks of 5-mm thickness were glued with toner, cut to the patient shape and assembled to a phantom. In a sample application study, both phantoms were examined with five different tube current settings. Images were reconstructed using filtered-back projection (FBP) and iterative reconstruction (AIDR 3D) with three strength levels. Dose length product (DLP), signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNRs) were analysed. Data were analysed using 2-way analysis of variance (ANOVA).Results: Both methods achieved anthropomorphic phantoms with detailed patient anatomy. The 3D printer yielded a precise reproduction of the external patient shape, but caused visible glue artefacts. Gluing with toner avoided these artefacts and yielded more flexibility with regard to phantom size. In the sample application study, non-inferior SNR and CNR and up to 83.7% lower DLP were achieved on the phantoms with AIDR 3D compared with FBP.Conclusions: Two methods for assembling radiopaque printed paper sheets to phantoms of individual patients are presented. The sample application demonstrates potential for simulation of patient imaging and systematic CT dose and image quality assessment.Key Points: • Two methods were developed to create realistic CT phantoms of individual patients from radiopaque printed paper sheets. • Analysis of five tube current and four reconstruction settings on two radiopaque 3D printed patient phantoms yielded non-inferior SNR and CNR and up to 83.7% lower dose with iterative reconstruction in comparison with filtered back projection. • Radiopaque 3D printed phantoms can simulate patients and allow systematic analysis of CT dose and image quality parameters. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method of generating the elemental image array (EIA) for the integral imaging (InIm) based light field display (LFD). Firstly, we reveal the intrinsic voxel spatial distributions of the InIm‐based LFD and analyze how the voxel space affects the display performances such as spatial resolution, depth of field, and smoothness of parallax. Then, we present an algorithm to generate an EIA from a pair of RGB and depth (RGBD) images and an optimally selected voxel space. In the experiments, we tested the display performances of the voxels on different depth planes and obtained results consistent with the theoretical analyses. We also experimented with a computer 3D model and a real‐world scene on two InIm‐based LFD prototypes working in different modes, one in real mode and the other in virtual mode, and obtained favorable 3D display effects. The proposed method simplifies the light field data acquisition and image synthesis process, and supports handling both the virtual and the real‐world 3D scenes. We expect the proposed system to help the practical application of the InIm‐based LFD technology. [ABSTRACT FROM AUTHOR]

Medical images have a very significant impact in the diagnosing and treating process of patient ailments and radiology applications. For many reasons, processing medical images can greatly improve the quality of radiologists' job. While 2D models have been in use for medical applications for decades, wide-spread utilization of 3D models appeared only in recent years. The proposed work in this paper aims to segment medical volumes under various conditions and in different axel representations. In this paper, we propose an algorithm for segmenting Medical Volumes based on Multiresolution Analysis. Different 3D volume reconstructed versions have been considered to come up with a robust and accurate segmentation results. The proposed algorithm is validated using real medical and Phantom Data. Processing time, segmentation accuracy of predefined data sets and radiologist's opinions were the key factors for methods validations. [ABSTRACT FROM AUTHOR]

Background: To conserve personal protective equipment (PPE) and reduce exposure to potentially infected COVID‐19 patients, several Californian facilities independently implemented a method of acquiring portable chest radiographs through glass barriers that was originally developed by the University of Washington. Methods: This work quantifies the transmission of radiation through a glass barrier using six radiographic systems at five facilities. Patient entrance air kerma (EAK) and effective dose were estimated both with and without the glass barrier. Beam penetrability and resulting exposure index (EI) and deviation index (DI) were measured and used to adjust the tube current‐time product (mAs) for glass barriers. Because of beam hardening, the contrast‐to‐noise ratio (CNR) was measured with image quality phantoms to ensure diagnostic integrity. Finally, scatter surveys were performed to assess staff radiation exposure both inside and outside the exam room. Results: The glass barriers attenuated a mean of 61% of the normal X‐ray beams. When the mAs was increased to match EI values, there was no discernible degradation of image quality as determined by the CNR. This was corroborated with subjective assessments of image quality by chest radiologists. The glass‐hardened beams acted as a filter for low energy X‐rays, and some facilities observed slight changes in patient effective doses. There was scattering from both the phantoms and the glass barriers within the room. Conclusions: Glass barriers require an approximate 2.5 times increase in beam intensity, with all other technique factors held constant. Further refinements are necessary for increased source‐to‐image distance and beam quality in order to adequately match EI values. This does not result in a significant increase in the radiation dose delivered to the patient. The use of lead aprons, mobile shields, and increased distance from scattering sources should be employed where practicable in order to keep staff radiation doses as low as reasonably achievable. [ABSTRACT FROM AUTHOR]

We used novel perceptual and oculomotor measures to understand the negative impacts of low (phantom array) and high (motion blur) duty cycles with a high‐speed, AR‐like HMD. We quantified this tradeoff and found that eye movements were adversely impacted by low duty cycles, even when no artifact was reported. [ABSTRACT FROM AUTHOR]

This paper studies the influence of illumination level of modulated light on the visibility of the phantom array effect under office lighting condition. Results indicate that, the phantom array effect is comparable at different illumination levels when the modulated light is driven by 100Hz waveforms, while the phantom array is more visible at higher illumination levels with 600Hz waveforms. [ABSTRACT FROM AUTHOR]

Background: To test and validate novel CT techniques, such as texture analysis in radiomics, repeat measurements are required. Current anthropomorphic phantoms lack fine texture and true anatomic representation. 3D‐printing of iodinated ink on paper is a promising phantom manufacturing technique. Previously acquired or artificially created CT data can be used to generate realistic phantoms. Purpose: To present the design process of an anthropomorphic 3D‐printed iodine ink phantom, highlighting the different advantages and pitfalls in its use. To analyze the phantom's X‐ray attenuation properties, and the influences of the printing process on the imaging characteristics, by comparing it to the original input dataset. Methods: Two patient CT scans and artificially generated test patterns were combined in a single dataset for phantom printing and cropped to a size of 26 × 19 × 30 cm3. This DICOM dataset was printed on paper using iodinated ink. The phantom was CT‐scanned and compared to the original image dataset used for printing the phantom. The water‐equivalent diameter of the phantom was compared to that of a patient cohort (N = 104). Iodine concentrations in the phantom were measured using dual‐energy CT. 86 radiomics features were extracted from 10 repeat phantom scans and the input dataset. Features were compared using a histogram analysis and a PCA individually and overall, respectively. The frequency content was compared using the normalized spectrum modulus. Results: Low density structures are depicted incorrectly, while soft tissue structures show excellent visual accordance with the input dataset. Maximum deviations of around 30 HU between the original dataset and phantom HU values were observed. The phantom has X‐ray attenuation properties comparable to a lightweight adult patient (∼54 kg, BMI 19 kg/m2). Iodine concentrations in the phantom varied between 0 and 50 mg/ml. PCA of radiomics features shows different tissue types separate in similar areas of PCA representation in the phantom scans as in the input dataset. Individual feature analysis revealed systematic shift of first order radiomics features compared to the original dataset, while some higher order radiomics features did not. The normalized frequency modulus |f(ω)| of the phantom data agrees well with the original data. However, all frequencies systematically occur more frequently in the phantom compared to the maximum of the spectrum modulus than in the original data set, especially for mid‐frequencies (e.g., for ω = 0.3942 mm−1, |f(ω)|original = 0.09 * |fmax|original and |f(ω)|phantom = 0.12 * |fmax|phantom). Conclusions: 3D‐iodine‐ink‐printing technology can be used to print anthropomorphic phantoms with a water‐equivalent diameter of a lightweight adult patient. Challenges include small residual air enclosures and the fidelity of HU values. For soft tissue, there is a good agreement between the HU values of the phantom and input data set. Radiomics texture features of the phantom scans are similar to the input data set, but systematic shifts of radiomics features in first order features, due to differences in HU values, need to be considered. The paper substrate influences the spatial frequency distribution of the phantom scans. This phantom type is of very limited use for dual‐energy CT analyses. [ABSTRACT FROM AUTHOR]

To optimize microbubble formulations for clinical applications, the size distribution, concentration, and acoustic intensity must be rapidly measurable to allow for the successful iteration of microbubble design. In this paper, a comprehensive method was developed to compare microbubble formulations with different lipid shell compositions using optical and acoustic methods of measurement to collect the size distribution, concentration, and mean scattering intensity. An open-source ImageJ macro code was modified for the selective counting and sizing of brightfield microbubble images. A high-throughput agarose phantom was designed to collect multiple scattering reflections of microbubble samples to estimate the echogenicity of each microbubble solution. The information contained in the size distribution and concentration, combined with the instantaneous scattering power, can identify modifications needed for prototyping specific microbubble formulations. [ABSTRACT FROM AUTHOR]

The dynamics of the complex shear modulus, G*, of soft biological tissue is governed by the rigidity and topology of multiscale mechanical networks. Multifrequency elastography can measure the frequency dependence of G* in soft biological tissue, providing information about the structure of tissue networks atmultiple scales. In this study, the viscoelastic properties of structuremimicking phantoms containing tangled paper stripes embedded in agarose gel are investigated by multifrequency magnetic resonance elastography within the dynamic range of 40-120 Hz. The effective media viscoelastic properties are analyzed in terms of the storage modulus (the real part of G*), the loss modulus (the imaginary part of G*) and the viscoelastic powerlaw given by the two-parameter springpot model. Furthermore, diffusion tensor imaging is used for investigating the effect of network structures on water mobility. The following observations were made: the random paper networks with fractal dimensions between 2.481 and 2.755 had no or minor effects on the storage modulus, whereas the loss modulus was significantly increased about 2.2 kPa per fractal dimension unit (R = 0.962, P < 0.01). This structural sensitivity of the loss modulus was significantly correlated with the springpot powerlaw exponent (0.965, P < 0.01), while for the springpot elasticity modulus, a trend was discernable (0.895, P < 0.05). No effect of the paper network on water diffusion was observed. The gel phantoms with embedded paper stripes presented here are a feasible way for experimentally studying the effect of network topology on soft-tissue viscoelastic parameters. In the dynamic range of in vivo elastography, the fractal network dimension primarily correlates to the loss behavior of soft tissue as can be seen from the loss modulus or the powerlaw exponent of the springpot model. These findings represent the experimental underpinning of structure-sensitive elastography for an improved characterization of various soft-tissue diseases. [ABSTRACT FROM AUTHOR]

Introduction: Medical phantoms play a crucial role in medical imaging and therapy. However, the successful development of these phantoms heavily relies on a comprehensive understanding of the requirements specific to each application. Methods: In this paper, we emphasize the significance of requirement analysis in medical phantom development and develop a novel approach for gathering and classifying requirements specific for phantom development. Results: The implemented survey tool is designed to accommodate the diverse needs of stakeholders involved in phantom development, including medical staff, physicists, engineers, and product developers. To validate the effectiveness of the approach, we conduct the development of a multimodal deformable pelvic phantom, providing insights into the process and its applicability. Discussion: The results demonstrate the utility and reliability of our approach in systematically gathering, categorizing, and prioritizing requirements, thus facilitating the streamlined and efficient development of medical phantoms. [ABSTRACT FROM AUTHOR]

In recent years, material extrusion-based additive manufacturing, particularly fused filament fabrication (FFF), has gained significant attention due to its versatility and cost-effectiveness in producing complex geometries. This paper presents the characterization of seven novel materials for FFF and twenty-two commercially available filaments in terms of X-ray computed tomography (CT) numbers, as tissue mimicking materials for the realization of 3D printed radiological phantoms. Two technical approaches, by 3D printing of cube samples and by producing cylinders of melted materials, are used for achieving this goal. Results showed that the CT numbers, given in Hounsfield unit (HU), of all the samples depended on the beam kilovoltage (kV). The CT numbers ranged from +411 HU to +3071 HU (at 80 kV), from −422 HU to +3071 HU (at 100 kV), and from −442 HU to +3070 HU (at 120 kV). Several commercial and custom-made filaments demonstrated suitability for substituting soft and hard human tissues, for realization of 3D printed phantoms with FFF in CT imaging. For breast imaging, an anthropomorphic phantom with two filaments could be fabricated using ABS-C (conductive acrylonitrile butadiene styrene) as a substitute for breast adipose tissue, and ASA-A (acrylic styrene acrylonitrile) for glandular breast tissue. [ABSTRACT FROM AUTHOR]

Recreating cerebral tissue using a tissue-mimicking phantom is valuable because it provides a tool for studying physiological and biological processes related to tissues without the necessity of performing the study directly in the tissue or even in a patient. The reproduction of the optical properties allows investigation in areas such as imaging, optics, and ultrasound, among others. This paper presents a methodology for manufacturing agarose-based phantoms that mimic the optical characteristics of brain tissue using scattering and absorbing agents and proposes combinations of these agents to recreate the healthy brain tissue optical coefficients within the wavelength range of 350 to 500 nm. The results of the characterization of the manufactured phantoms propose ideal combinations of the used materials for their use in controlled environment experiments in the UV range, following a cost-effective methodology. [ABSTRACT FROM AUTHOR]

Ultrasound elastography has been available on most modern systems; however, the implementation of quality processes tends to be ad hoc. It is essential for a medical physicist to benchmark elastography measurements on each system and track them over time, especially after major software upgrades or repairs. This study aims to establish baseline data using phantoms and monitor them for quality assurance in elastography. In this paper, we utilized two phantoms: a set of cylinders, each with a composite material with varying Young's moduli, and an anthropomorphic abdominal phantom containing a liver modeled to represent early-stage fibrosis. These phantoms were imaged using three ultrasound manufacturers' elastography functions with either point or 2D elastography. The abdominal phantom was also imaged using magnetic resonance elastography (MRE) as it is recognized as the non-invasive gold standard for staging liver fibrosis. The scaling factor was determined based on the data acquired using MR and US elastography from the same vendor. The ultrasound elastography measurements showed inconsistency between different manufacturers, but within the same manufacturer, the measurements showed high repeatability. In conclusion, we have established baseline data for quality assurance procedures and specified the criteria for the acceptable range in liver fibrosis phantoms during routine testing. [ABSTRACT FROM AUTHOR]

Purpose Physical phantoms are central to the evaluation of 2D and 3D breast-imaging systems. Currently, available physical phantoms have limitations including unrealistic uniform background structure, large expense, or excessive fabrication time. The purpose of this work is to outline a method for rapidly creating realistic, inexpensive physical anthropomorphic phantoms for use in full-field digital mammography ( FFDM) and digital breast tomosynthesis ( DBT). Methods The phantom was first modeled using analytical expressions and then discretized into voxels of a specified size. The interior of the breast was divided into glandular and adipose tissue classes using Voronoi segmentation, and additional structures like blood vessels, chest muscle, and ligaments were added. The physical phantom was then fabricated from the virtual model in a slice by slice fashion through inkjet printing, using parchment paper and a radiopaque ink containing 33% (I33%) or 25% (I25%) iohexol by volume. Three types of parchment paper (P1, P2, and P3) were examined. The phantom materials were characterized in terms of their effective linear attenuation coefficients ( μeff) using full-field digital mammography ( FFDM) and their energy-dependent linear attenuation coefficients ( μ(E)) using a spectroscopic energy discriminating detector system. The printing method was further validated on the basis of accuracy, print consistency, and the reproducibility of ink batches. Results The μeff of two types of parchment paper were close to that of adipose tissue, with μeff = 0.61 ± 0.05 cm−1 for P1, 0.61 ± 0.04 cm−1 for P2, and 0.57 ± 0.03 cm−1 for adipose tissue. The addition of the iodinated ink increased the effective attenuation to that of glandular tissue, with μeff = 0.89 ± 0.06 cm−1 for P1 + I25% and 0.94 ± 0.06 cm−1 for P1 + I33% compared to 0.90 ± 0.03 cm−1 for glandular tissue. Spectroscopic measurements showed a good match between the parchment paper and reference values for adipose and glandular tissues across photon energies. Good accuracy was found between the model and the printed phantom by comparing a FFDM of the virtual model simulated through Monte Carlo with a real FFDM of the fully printed phantom. High consistency was found over multiple prints, with 3% variability in mean ink signal across various samples. Reproducibility of ink consistency was very high with <1% variation signal from multiple batches of ink. Imaging of the phantom using FFDM and DBT systems showed promising utility for 2D and 3D imaging. Conclusions A novel, realistic breast phantom can be created using an analytically defined breast model and readily available materials. The work provides a method to fabricate any virtual phantom in a manner that is accurate, inexpensive, easily accessible, and can be made with different materials or breast models. [ABSTRACT FROM AUTHOR]

Innovations in biomedical ultrasonics cannot be materialized without foundational advances in experimental methods, tools, protocols. For instance, innovations in ultrasound imaging are often backed up by various investigative and validation tools including, but not limited to: 1) simulation programs, 2) phantom fabrication techniques, and 3) real-time computing frameworks. In the emerging field of therapeutic ultrasound, fundamental advances in engineering methods have also made significant contributions to the discipline's technical progress. Well-known examples include: 1) techniques for synthesizing microbubbles and nanodroplets, 2) rational design approaches for acoustic exposure instruments, and 3) establishment of suitable cellular and animal models to therapeutic ultrasound experimentation. Nevertheless, these essential techniques and protocols have not always been reported in depth, and many technical details have been relegated as black-box processes in research articles. There is a dire need for a more concentrated effort on the reporting of the key methods used in contemporary biomedical ultrasound research. [ABSTRACT FROM AUTHOR]

The Magnetic Pulse Compression (MPC) system is a well-established method for generating high-peak-power, short-duration voltage pulses, commonly used in pulse power supplies (PPS). Traditionally designed for a fixed high repetition rate, this paper explores the techniques and outcomes of variable repetition rate operation in an MPC-based PPS used to excite a copper vapor laser (CVL). Specifically, the PPS, initially designed for 9 kHz operation, is tested at three different rates: 8 kHz, 9 kHz, and 10 kHz. A mathematical model is developed, and experimental modifications are presented in this paper. The study investigates the impact of repetition rate variations on CVL parameters, particularly phantom current (Phantom current: 47% at 8 kHz, 54% at 9 kHz, and 51% at 10 kHz). Phantom current reduces at 10 kHz due to improved impedance matching. At 8 kHz, the laser output is 24W, increases to 30W at 9 kHz and 43W at 10 kHz with a plane-plane resonator configuration. This trend extends to the master oscillator power amplifier (MOPA) at 10 kHz, resulting in a 50% increase in optical power output compared to 9 kHz. This improvement at 10 kHz applies to various parameters, including optical pulse characteristics, average power, electro-optic efficiency, energy per pulse, reduced jitter, and impedance matching. [ABSTRACT FROM AUTHOR]

3D city models are fast becoming a key factor for planning, design and analysis in the AEC industry, and urban informatics. Data are being acquired from a variety of sources and each consequent representation contains inherent information about its location, geometry, structure and usability. These digital representations can range from unstructured models with very little semantic data such as 3D point clouds, and 3D mesh models or they can be highly structured and semantically enriched models following CityGML and IFC/BIM standards. Matching these diverse representations against one another can facilitate information flow and eventually lead to a coherent interconnected Digital twin. Consistency measures would be needed to compare one representation against another. For comparison of any kind, a common baseline needs to be established. A tentative approach, as outlined in this paper, is to convert all the model types into a common representation such as 'volumetric pixels' or 'voxels' but the concept of 'voxel' as we know it, is not enough to deal with the rich semantic and organizational structure of modelling representations such as IFC and CityGML. Voxelisation is a complex process and conventional conversion methods concentrate on translating the geometry between representation types but the semantic and class hierarchy information is usually not translated. This paper assesses the need for matching 3D models using a common representation (voxels), discusses the challenges of the voxelisation process and proposes the concept of a 'RichVoxel'. [ABSTRACT FROM AUTHOR]

In this paper, SEPAM_HRNet, a high-resolution pose-estimation model that incorporates the squeeze-and-excitation and pixel-attention-mask (SEPAM) module is proposed. Feature pyramid extraction, channel attention, and pixel-attention masks are integrated into the SEPAM module, resulting in improved model performance. The construction of the model involves replacing ordinary convolutions with the plug-and-play SEPAM module, which leads to the creation of the SEPAMneck module and SEPAMblock module. To evaluate the model's performance, the YOGA2022 human yoga poses teaching dataset is presented. This dataset comprises 15,350 images that capture ten basic yoga pose types—Warrior I Pose, Warrior II Pose, Bridge Pose, Downward Dog Pose, Flat Pose, Inclined Plank Pose, Seated Pose, Triangle Pose, Phantom Chair Pose, and Goddess Pose—with a total of five participants. The YOGA2022 dataset serves as a benchmark for evaluating the accuracy of the human pose-estimation model. The experimental results demonstrated that the SEPAM_HRNet model achieved improved accuracy in predicting human keypoints on both the common objects in context (COCO) calibration set and the YOGA2022 calibration set, compared to other state-of-the-art human pose-estimation models with the same image resolution and environment configuration. These findings emphasize the superior performance of the SEPAM_HRNet model. [ABSTRACT FROM AUTHOR]

Dental aerosol-generating procedures produce a large amount of splatters and aerosols that create a major concern for airborne disease transmission, such as COVID-19. This study established a method to visualise splatter and aerosol contamination by common dental instrumentation, namely ultrasonic scaling, air-water spray, high-speed and low-speed handpieces. Mock dental procedures were performed on a mannequin model, containing teeth in a typodont and a phantom head, using irrigation water containing fluorescein dye as a tracer. Filter papers were placed in 10 different locations to collect splatters and aerosols, at distances ranging from 20 to 120 cm from the source. All four types of dental equipment produced contamination from splatters and aerosols. At 120 cm away from the source, the high-speed handpiece generated the greatest amount and size (656 ± 551 μm) of splatter particles, while the triplex syringe generated the largest amount of aerosols (particle size: 1.73 ± 2.23 μm). Of note, the low-speed handpiece produced the least amount and size (260 ± 142 μm) of splatter particles and the least amount of aerosols (particle size: 4.47 ± 5.92 μm) at 120 cm. All four dental AGPs produce contamination from droplets and aerosols, with different patterns of distribution. This simple model provides a method to test various preventive strategies to reduce risks from splatter and aerosols. [ABSTRACT FROM AUTHOR]

Using liver phantoms for mimicking human tissue in clinical training, disease diagnosis, and treatment planning is a common practice. The fabrication material of the liver phantom should exhibit mechanical properties similar to those of the real liver organ in the human body. This tissue-equivalent material is essential for qualitative and quantitative investigation of the liver mechanisms in producing nutrients, excretion of waste metabolites, and tissue deformity at mechanical stimulus. This paper reviews the mechanical properties of human hepatic tissues to develop liver-mimicking phantoms. These properties include viscosity, elasticity, acoustic impedance, sound speed, and attenuation. The advantages and disadvantages of the most common fabrication materials for developing liver tissue-mimicking phantoms are also highlighted. Such phantoms will give a better insight into the real tissue damage during the disease progression and preservation for transplantation. The liver tissue-mimicking phantom will raise the quality assurance of patient diagnostic and treatment precision and offer a definitive clinical trial data collection. [ABSTRACT FROM AUTHOR]

For reconstructing large tomographic datasets fast, filtered backprojection‐type or Fourier‐based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. The continuous mathematical formulas used for image reconstruction in such algorithms are unambiguous. However, variations in discretization and interpolation result in quantitative differences between reconstructed images, and corresponding segmentations, obtained from different software. This hinders reproducibility of experimental results, making it difficult to ensure that results and conclusions from experiments can be reproduced at different facilities or using different software. In this paper, a way to reduce such differences by optimizing the filter used in analytical algorithms is proposed. These filters can be computed using a wrapper routine around a black‐box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. Use cases for this approach are demonstrated by computing implementation‐adapted filters for several open‐source implementations and applying them to simulated phantoms and real‐world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline. [ABSTRACT FROM AUTHOR]

This paper is about dynamical modeling of an electroencephalographic (EEG) measurement chain. It is based on a home-made experimental setup consisting of an electrolytic medium, stimulated by external electrodes, the activity of which is measured at different points via other electrodes, connected to an EEG recording device. A novel noninteger-order model structure is then established with a so-called constant phase element, and a Nyquist-based graphical method is derived to identify the noninteger order. The study is completed with a recursive identification method for full parameter estimation in the model, and various applications on experimental data are presented, finally resulting in a fully identified noninteger order high-pass filter. [ABSTRACT FROM AUTHOR]

Automotive traffic scenes are complex due to the variety of possible scenarios, objects, and weather conditions that need to be handled. In contrast to more constrained environments, such as automated underground trains, automotive perception systems cannot be tailored to a narrow field of specific tasks but must handle an ever-changing environment with unforeseen events. As currently no single sensor is able to reliably perceive all relevant activity in the surroundings, sensor data fusion is applied to perceive as much information as possible. Data fusion of different sensors and sensor modalities on a low abstraction level enables the compensation of sensor weaknesses and misdetections among the sensors before the information-rich sensor data are compressed and thereby information is lost after a sensor-individual object detection. This paper develops a low-level sensor fusion network for 3D object detection, which fuses lidar, camera, and radar data. The fusion network is trained and evaluated on the nuScenes data set. On the test set, fusion of radar data increases the resulting AP (Average Precision) detection score by about 5.1% in comparison to the baseline lidar network. The radar sensor fusion proves especially beneficial in inclement conditions such as rain and night scenes. Fusing additional camera data contributes positively only in conjunction with the radar fusion, which shows that interdependencies of the sensors are important for the detection result. Additionally, the paper proposes a novel loss to handle the discontinuity of a simple yaw representation for object detection. Our updated loss increases the detection and orientation estimation performance for all sensor input configurations. The code for this research has been made available on GitHub. [ABSTRACT FROM AUTHOR]

The development of cuffless blood pressure monitoring devices has been attracting attention in the field of medical devices. Measuring the diameter of blood vessels based on the A-mode waveform obtained by an ultrasound sensor attached to the body surface is suitable for daily blood pressure monitoring because of the simplicity of the device. However, movement by the user can cause device displacement, which reduces the received intensity of the wave reflected from the blood vessel wall, resulting in the incorrect measurement of the blood vessel diameter. To solve this problem, we previously proposed a blood vessel diameter sensor with an acoustic lens that transmits and receives ultrasound waves within a certain angular range along the long axis of the blood vessel, and verified the improved robustness of blood vessel diameter measurement compared with that with a planar sensor. The design of blood vessel diameter sensors requires the consideration of reflections and artifacts other than the blood vessel wall, and the use of simulation technology helps in efficient design. In this paper, we describe a simulation model for a blood vessel diameter sensor to support the design process. The simulation model was evaluated using an experimental blood vessel model (phantom) with characteristics similar to those for a human body, and the experimental and simulation results were found to be in agreement in terms of the angular range over which blood vessel diameters can be accurately measured and the effects of reflections and artifacts other than blood vessels. The simulation model is expected to accelerate our understanding of the effects of noise factors and the investigation of the causes of problems and improvements. [ABSTRACT FROM AUTHOR]

At the Czech Technical University in Prague, we have installed virtual software environment simulating a radiotherapy treatment room with a medical linear accelerator (software VERT and VERT Physics by Vertual Ltd., United Kingdom). It is possible to simulate patient treatment and physics QA (quality assurance) measurements in virtual reality. This is beneficial for our students and teachers because there is no radiation present while doing the exercises and it is accessible at any time, unlike medical linear accelerators at hospitals. For our department, we have chosen the TrueBeam model by Varian Medical Systems, USA. The linear accelerator can be operated by the user in the same way as at the hospital, including the hardware pendant. There is a selection of patient treatment plans, CT images and RT structures, all of which can be visualised inside the treatment room, also during beam on, simulating the situation inside the patient while irradiating the tumour. Any DICOM files, even from another manufacturer's linac (linear accelerator) or treatment planning system, can be imported into VERT. Apart from this, there is also an imaging interface and cone-beam CT interface showing options for patient setup. Another part of the software is a physics module with various phantoms and detectors for dosimetry as well as geometry tests. For example, a large water tank can be used for relative dosimetry of photon beams (percent depth doses and profiles), a smaller water phantom can be used for reference dosimetry or chamber cross calibration according to the TRS 398 (1) or IPEM (2) protocol. The results of measurements are based on look-up tables coming from real beam data, so dependence on the depth of measurement, field size, temperature and pressure and other parameters can be demonstrated. Moreover, it is possible to introduce many types of errors into the linac, such as jaw position, laser, or collimator miscalibration, and show how these errors propagate to patient irradiation and how they can be detected by QA tools. This paper is a short report on how this system has been used at our university and how it might be used in modern learning, pointing out its advantages and drawbacks. At the 16th Workshop on European Collaboration in Higher Education on Radiological and Nuclear Engineering and Radiation Protection (CHERNE) it was proposed that this virtual system could be used for an international student training course on medical physics in radiotherapy within the CHERNE network. This course might contain theoretical lectures with demonstrations on the virtual linac, practical exercises on the virtual linac and visits to hospitals (a photon radiotherapy centre, the Thomayer University Hospital in particular, and a proton therapy centre). [ABSTRACT FROM AUTHOR]

Background: The Tomosynthesis Mammography Imaging Screening Trial (TMIST), EA1151 conducted by the Eastern Cooperative Oncology Group (ECOG)/American College of Radiology Imaging Network (ACRIN) is a randomized clinical trial designed to assess the effectiveness for breast cancer screening of digital breast tomosynthesis (TM) compared to digital mammography (DM). Equipment from multiple vendors is being used in the study. Purpose: For the findings of the study to be valid and capture the true capacities of the two technology types, it is important that all equipment is operated within appropriate parameters with regard to image quality and dose. A harmonized QC program was established by a core physics team. Since there are over 120 trial sites, a centralized, automated QC program was chosen as the most practical design. This report presents results of the weekly QC testing program. A companion paper will review quality monitoring based on data from the headers of the patient images. Methods: Study images are collected centrally after de‐identification using the "TRIAD" application developed by ACR. The core physics team devised and implemented a minimal set of quality control (QC) tests to evaluate the tomosynthesis and 2D mammography systems. Weekly, monthly and annual testing is performed by the site mammography technologists with images submitted directly to the physics core. The weekly physics QC tests are described: SDNR of a low‐contrast mass object, artifact spread, spatial resolution, tracking of technical factors, and in‐slice noise power spectra. Results: As of December 31, 2022 (5 years), 145 sites with 411 machines had submitted QC data. A total of 136 742 TMIST participant screening imaging studies had been performed. The 5th and 95th percentile mean glandular doses for a single tomosynthesis exposure to a 4.0 cm thick PMMA phantom ("standard breast phantom") were 1.24 and 1.68 mGy respectively. The largest sources of QC non‐conformance were: operator error, not following the QC protocol exactly, unreported software updates and preventive maintenance activities that affected QC setpoints. Noise power spectra were measured, however, standardization of performance targets across machine types and software revisions was difficult. Nevertheless, for each machine type, test measurement results were very consistent when the protocol was followed. Deviations in test results were mostly related to software and hardware changes. Conclusion: Most systems performed very consistently. Although this is a harmonized program using identical phantoms and testing protocols, it is not appropriate to apply universal threshold or target metrics across the machine types because the systems have different non‐linear reconstruction algorithms and image display filters. It was found to be more useful to assess pass/fail criteria in terms of relative deviations from baseline values established when a system is first characterized and after equipment is changed. Generally, systems which needed repair failed suddenly, but in retrospect, for a few cases, drops in SDNR and increases in mAs were observed prior to tube failure. TMIST is registered as NCT03233191 by Clinicaltrials.gov [ABSTRACT FROM AUTHOR]

In this paper we consider radar approaches for breast cancer detection. The aim is to give a brief review of the main features of incoherent methods, based on beam-forming and Multiple SIgnal Classification (MUSIC) algorithms, that we have recently developed, and to compare them with classical coherent beam-forming. Those methods have the remarkable advantage of not requiring antenna characterization/compensation, which can be problematic in view of the close (to the breast) proximity set-up usually employed in breast imaging. Moreover, we proceed to an experimental validation of one of the incoherent methods, i.e., the I-MUSIC, using the multimodal breast phantom we have previously developed. While in a previous paper we focused on the phantom manufacture and characterization, here we are mainly concerned with providing the detail of the reconstruction algorithm, in particular for a new multi-step clutter rejection method that was employed and only barely described. In this regard, this contribution can be considered as a completion of our previous study. The experiments against the phantom show promising results and highlight the crucial role played by the clutter rejection procedure. [ABSTRACT FROM AUTHOR]

Voxels have been used in various application domains successfully for the last several decades. Their main advantage is the underlying discrete data structure allowing to reliably work with surrounding voxels all the time. In this paper, capabilities of the Unity game engine for voxels management and geometry voxelisation are assessed, where 4 native solutions and 7 open-source projects written for Unity are investigated. Although many voxel-based options exist in Unity, they only deal with one part related to voxels. Therefore, the available capabilities to voxelise, visualise, structure and export voxels are combined and extended with the goal of successfully processing large 3D models and geometries. Many voxel visualisation techniques are investigated including mesh, VFX, point clouds and SVO, which have distinctive benefits in various aspects. Possibilities to structure voxels for effective management in simulations and other tasks are shown. Also, it is enabled to export voxels as point clouds and to the Postgres database for further processing, spatial analysis and distribution. One of the main conclusions is the lack of support for state-of-the-art voxel data structures, where the presented platform can easily be extended to support any. This platform can be used by people who deal with 3D discrete data, require voxelising 3D data, visualise voxels in different ways and technologies, as well as manage more efficiently sparsely occupied voxels. [ABSTRACT FROM AUTHOR]

A new reference resistive-capacitive voltage divider is presented in this paper, operating in dc and ac from 10 to 200 kHz. The ratio error is lower than 0.1% and the phase error is lower than $400~\mu $ rad (1.375’) at 100 kHz. The divider is stable and repeatable. The scale factor (SF) and the phase error repeatability, tested in 24-h continuous measurements repeated during 15 weeks, show an SF variation lower than 80 ppm and a phase error variation lower than 20 $\mu $ rad. This allows one to define a calibration matrix of the device bringing its relative measurement uncertainty lower than $0.5 \cdot 10^{-3}$. The divider calibration has been obtained with a step-up method, which could improve traceability in many laboratories and is described in this paper. The divider can be embedded in a calibration chain to test the accuracy of voltage transducers in the measurement of the ac voltage ripple, in the presence of a significant dc component, as it occurs in many power electronic systems. The voltage calibration chain is based on the use of the reference divider and a voltage injector, the secondary of which is placed in series with a stable dc source. By means of this calibration system, one of the best commercial voltage transducers on the market has been analyzed. This paper also highlights how the proposed voltage calibration chain could be used in perspective in a phantom power system for the development of a dc plus ac power standard. [ABSTRACT FROM AUTHOR]

Purpose: To make an adaptable, head shaped radionuclide phantom to simulate molecular imaging of the brain using clinical acquisition and reconstruction protocols. This will allow the characterization and correction of scanner characteristics, and improve the accuracy of clinical image analysis, including the application of databases of normal subjects. Methods: A fused deposition modeling 3D printer was used to create a head shaped phantom made up of transaxial slabs, derived from a simulated MRI dataset. The attenuation of the printed polylactide (PLA), measured by means of the Hounsfield unit on CT scanning, was set to match that of the brain by adjusting the proportion of plastic filament and air (fill ratio). Transmission measurements were made to verify the attenuation of the printed slabs. The radionuclide distribution within the phantom was created by adding 99mTc pertechnetate to the ink cartridge of a paper printer and printing images of gray and white matter anatomy, segmented from the same MRI data. The complete subresolution sandwich phantom was assembled from alternate 3D printed slabs and radioactive paper sheets, and then imaged on a dual headed gamma camera to simulate an HMPAO SPECT scan. Results: Reconstructions of phantom scans successfully used automated ellipse fitting to apply attenuation correction. This removed the variability inherent in manual application of attenuation correction and registration inherent in existing cylindrical phantom designs. The resulting images were assessed visually and by count profiles and found to be similar to those from an existing elliptical PMMA phantom. Conclusions: The authors have demonstrated the ability to create physically realistic HMPAO SPECT simulations using a novel head-shaped 3D printed subresolution sandwich method phantom. The phantom can be used to validate all neurological SPECT imaging applications. A simple modification of the phantom design to use thinner slabs would make it suitable for use in PET. [ABSTRACT FROM AUTHOR]

Many new clinical investigations of microwave breast imaging have been published in recent years. Trials with over one hundred participants have indicated the potential of microwave imaging to detect breast cancer, with particularly encouraging sensitivity results reported from women with dense breasts. The next phase of clinical trials will involve larger and more diverse populations, including women with no breast abnormalities or benign breast diseases. These trials will need to address clinical efficacy in terms of sensitivity and specificity. A number of challenges exist when using microwave imaging with broad populations: 1) addressing the substantial variance in breast composition observed in the population and 2) achieving high specificity given differences between individuals. This paper analyses these challenges using a diverse phantom set which models the variance in breast composition and tumor shape and size seen in the population. The data show that the sensitivity of microwave breast imaging in breasts of differing density can suffer if patient-specific beamforming is not used. Moreover, the results suggest that achieving high specificity in dense breasts may be difficult, but that patient-specific beamforming does not adversely affect the expected specificity. In summary, this paper finds that patient-specific beamforming has a tangible impact on expected sensitivity in experimental cases and that achieving high specificity in dense breasts may be challenging. [ABSTRACT FROM AUTHOR]

Objectives: To develop an anthropomorphic phantom closely mimicking patient anatomy and to evaluate the phantom for the simulation of computed tomography (CT)-guided procedures.Methods: Patient CT images were printed with aqueous potassium iodide solution (1 g/mL) on paper. The printed paper sheets were stacked in alternation with 1-mm thick polyethylene foam layers, cut to the patient shape and glued together to create an anthropomorphic abdomen phantom. Ten interventional radiologists performed periradicular infiltration on the phantom and rated the phantom procedure regarding different aspects of suitability for simulating CT-guided procedures.Results: Radiopaque printing in combination with polyethylene foam layers achieved a phantom with detailed patient anatomy that allowed needle placement. CT-guided periradicular infiltration on the phantom was rated highly realistic for simulation of anatomy, needle navigation and overall course of the procedure. Haptics were rated as intermediately realistic. Participants strongly agreed that the phantom was suitable for training and learning purposes.Conclusions: A radiopaque 3D printed, anthropomorphic phantom provides a realistic platform for the simulation of CT-guided procedures. Future work will focus on application for training and procedure optimisation.Key Points: • Radiopaque 3D printing combined with polyethylene foam achieves patient phantoms for CT-guided procedures. • Radiopaque 3D printed, anthropomorphic phantoms allow realistic simulation of CT-guided procedures. • Realistic visual guidance is a key aspect in simulation of CT-guided procedures. • Three-dimensional printed phantoms provide a platform for training and optimisation of CT-guided procedures. [ABSTRACT FROM AUTHOR]

The basic emission process associated with positron emission tomography (PET) imaging is Poisson in nature. Reconstructed images inherit some aspects of this—regional variability is typically proportional to the regional mean. Iterative reconstruction using expectation–maximization (EM), widely used in clinical imaging now, imposes positivity constraints that impact noise properties. This paper is motivated by the analysis of data from a physical phantom study of a PET/CT scanner in routine clinical use. Both traditional filtered back-projection (FBP) and EM reconstructions of the images are considered. FBP images are quite Gaussian, but the EM reconstructions exhibit Gamma-like skewness. The Gamma structure has implications for how reconstructed PET images might be processed statistically. Post-reconstruction inference—model fitting and diagnostics for regions of interest are of particular interest. Although the relevant Gamma parameterization is not within the framework of generalized linear models (GLM), iteratively re-weighted least squares (IRLS) techniques, which are often used to find the maximum likelihood estimates of a GLM, can be adapted for analysis in this setting. This paper highlights the use of a Gamma-based probability transform in producing normalized residuals as model diagnostics. The approach is demonstrated for quality assurance analyses associated with physical phantom studies—recovering estimates of local bias and variance characteristics in an operational scanner. Numerical simulations show that when the Gamma assumption is reasonable, gains in efficiency are obtained. This paper shows that the adaptation of standard analysis methods to accommodate the Gamma structure is straightforward and beneficial. [ABSTRACT FROM PUBLISHER]

Abstract: This paper describes Development of a Phantom for Tomosynthesis with Potential for Automated Analysis via the Cloud. Several studies are underway to investigate the effectiveness of Tomosynthesis Mammographic Image Screening, including the large TMIST project as funded by the National Cancer Institute https://www.cancer.gov/about-cancer/treatment/clinical-trials/nci-supported/tmist. The development of the phantom described in this paper follows initiatives from the FDA, the AAPM TG245 task group, and European Reference Organization (EUREF) for Quality Assured Breast Screening and Diagnostic Services Committee report noting, that no formal endorsement nor recommendation for use has been sought, or granted by any of these groups. This paper reports on the possibility of using this newly developed Tomosynthesis Phantom for Quality Assurance, field testing of image performance, including remote monitoring of DBT system performance, e.g., via transmission over the cloud. The phantom includes tests for: phantom positioning and alignment (important for remote analysis), scan geometry (x and y), chest wall offset, scan slice width and Slice Sensitivity Profile (SSP(z)) slice geometry (slice width), scan slice incrementation (z), z axis geometry bead, low contrast detectability using low contrast spheres, spatial resolution via Point Spread Function (PSF), Image uniformity, Signal to Noise Ratio (SNR), and Contrast to Noise Ratio (CNR) via readings over an Aluminum square. The phantom is designed for use with automated analysis via transmission of images over the cloud and the analysis package includes test of positioning accuracy (roll, pitch, and yaw). Data are shown from several commercial Tomosynthesis Scanners including Fuji, GE, Hologic, IMS‐Giotti, and Siemens; however, the focus of this paper is on phantom design, and not in general aimed at direct commercial comparisons, and wherever possible the identity of the data is anonymized. Results of automated analysis of the phantom are shown, and it is demonstrated that reliable analysis of such a phantom can be achieved remotely, including transmission of data through the cloud. [ABSTRACT FROM AUTHOR]

In this paper, a compact, flexible Vivaldi antenna is designed, and an array of nine identical antennas of this type is used as a microwave breast imaging model to detect cancerous tumors in the multilayers phantom model presented in this paper. The nine-antenna array is used to measure the backscattering signal of the breast phantom, where one antenna acts as a transmitter and the other eight antennas act as receivers of the scattered signals. Then, the second antenna is used as a transmitter and the other antennas as receivers, and so on till we have gone through all the antennas. These collected backscattered signals are used to reconstruct the image of the breast phantom using software called "Microwave Radar-based Imaging Toolbox (MERIT)". From the reconstructed image, the tumor inside the breast model can be identified and located. Different tumor sizes in different locations are tested, and it is found that the locations can be determined irrespective of the tumor size. The proposed modified Vivaldi antenna has a very compact size of 25 × 20 × 0.1 mm3 and has a different geometry compared with conventional Vivaldi antennas. The first version of the antenna has two resonant frequencies at 4 and 9.4 GHz, and because we are interested more in the first band, where it gives us sufficient resolution, we have notched the second frequency by etching two slots in the ground plane of the antenna and adding two rectangular parasitic elements on the radiating side of the antenna. This technique is utilized to block the second frequency at 9.4 GHz, and, as a result, the bandwidth of the first resonant frequency is enhanced by 20% compared with the first design bandwidth. The modified antenna is fabricated on Polyimide flexible material 0.1 mm thick with a dielectric constant of 3.5 using a standard PCB manufacturing process. The measured performance of this antenna is compared with the simulated results using the commercially available simulation software Ansoft HFSS, and it is found that the measured results and the simulated results are in good agreement. [ABSTRACT FROM AUTHOR]

This paper develops the model of the joint phantom track deception and the joint techniques of time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) localization to deceive air defense radar networks under the condition that an unmanned aerial vehicle (UAV) swarm has no prior knowledge of the radars' precise locations, and related performance experiment and analysis are presented to demonstrate the effectiveness of the proposed method and to clarify the influence factors of phantom track deception. The main contributions of this paper are as follows. Firstly, the model of phantom track deception against a radar network by UAV swarm without prior knowledge of the radars' positions are established. Secondly, TDOA/FDOA are adapted to locate networked enemy radars using UAV swarm, where the Fisher information matrix (FIM) is derived to evaluate the estimation accuracy. Thirdly, the uncertainty analysis consisting of radar location error and UAV position error is deduced. With these efforts, the integrated capability of sensing and jamming is realized. Moreover, the same source testing using space resolution cell (SRC) from the perspective of a radar network is executed to provide guidance for phantom track design. Finally, performance experiment and analysis are given to verify the theoretical analysis with simulation results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate two deep learning approaches to recovering initial temperature profiles from thermographic images in non-destructive material testing. First, we trained a deep neural network (DNN) in an end-to-end fashion by directly feeding the surface temperature measurements to the DNN. Second, we turned the surface temperature measurements into virtual waves (a recently developed concept in thermography), which we then fed to the DNN. To demonstrate the effectiveness of these methods, we implemented a data generator and created a dataset comprising a total of 100 000 simulated temperature measurement images. With the objective of determining a suitable baseline, we investigated several state-of-the-art model-based reconstruction methods, including Abel transformation, curvelet denoising, and time- and frequency-domain synthetic aperture focusing techniques. Additionally, a physical phantom was created to support evaluation on completely unseen real-world data. The results of several experiments suggest that both the end-to-end and the hybrid approach outperformed the baseline in terms of reconstruction accuracy. The end-to-end approach required the least amount of domain knowledge and was the most computationally efficient one. The hybrid approach required extensive domain knowledge and was more computationally expensive than the end-to-end approach. However, the virtual waves served as meaningful features that convert the complex task of the end-to-end reconstruction into a less demanding undertaking. This in turn yielded better reconstructions with the same number of training samples compared to the end-to-end approach. Additionally, it allowed more compact network architectures and use of prior knowledge, such as sparsity and non-negativity. The proposed method is suitable for non-destructive testing (NDT) in 2D where the amplitudes along the objects are considered to be constant (e.g., for metallic wires). To encourage the development of other deep-learning-based reconstruction techniques, we release both the synthetic and the real-world datasets along with the implementation of the deep learning methods to the research community. [ABSTRACT FROM AUTHOR]

Abdominal hemorrhage is an important clinical disease that can be life-threatening in severe cases. Therefore, timely detection and treatment of abdominal hemorrhage is crucial for the health and safety of patients. Magnetic induction tomography is a non-invasive, nonradioactive, and non-contact electromagnetic imaging technology with potential application value for disease screening and continuous monitoring. In this paper, a simulation model of electrical impedance distribution close to the real human abdominal tissue was constructed, and based on this model, the magnetic induction tomography simulation method of internal bleeding was studied by the finite element numerical method, and the comparison was verified by phantom experiments. The eddy current density distribution inside the abdominal tissue and the magnetic induction phase data at the tissue boundary are solved, and sensitivity analysis of phase differences caused by changes in the radius and position of bleeding volume was conducted, and three sensitivity indicators were proposed. Both the simulation and phantom experiment show that when there are six types of tissues with different conductivity in the abdomen, the radius of bleeding increases from 10 to 30 mm, and the radius phase difference sensitivity index Ar increases approximately linearly monotonically. Its radius transformation sensitivity Kr is 3.0961 × 10−5°/cm. When the position of the bleeding volume changes, the sensitivity index Ax of the x-axis displacement phase difference shows a quasilinear monotonic decrease, and the x-axis displacement sensitivity Kx is −6.3744 × 10−6°/cm. The y-axis displacement phase difference sensitivity Ay index shows a quasilinear relationship and monotonically increases, with a y-axis displacement sensitivity Ky of 5.2870 × 10−4°/cm. The results indicate that the phase difference sensitivity before and after the occurrence of bleeding can be used as a quantitative monitoring indicator to monitor the occurrence and trend of intra-abdominal hemorrhage, laying the foundation for the preliminary screening and continuous monitoring of abdominal hemorrhage diseases using magnetic induction imaging. [ABSTRACT FROM AUTHOR]

Background: Simulations of physical processes and behavior can provide unique insights and understanding of real‐world problems. Magnetic Resonance Imaging (MRI) is an imaging technique with several components of complexity. Several of these components have been characterized and simulated in the past. However, several computational challenges prevent simulations from being simultaneously fast, flexible, and accurate. Purpose: The simulation of MRI experiments is underutilized by medical physicists and researchers using currently available simulators due to reasons including speed, accuracy, and extensibility constraints. This paper introduces an innovative MRI simulation engine and framework that aims to overcome these issues making available realistic and fast MRI simulation. Methods: Using the CUDA C/C++ programing language, an MRI simulation engine (PhoenixMR), incorporating a Turing‐complete virtual machine (VM) to simulate abstract spatiotemporal complexities, was developed. This engine solves a set of time‐discrete Bloch equations using the symmetric operator splitting technique. An extensible front‐end framework package (written in Python) aids the use of PhoenixMR to simplify simulation development. Results: The PhoenixMR library and front‐end codes have been developed and tested. A set of example simulations were performed to demonstrate the ease of use and flexibility of simulation components such as geometrical setup, pulse sequence design, phantom design, and so forth. Initial validation of PhoenixMR is performed by comparing its accuracy and performance against a widely used MRI simulator using identical simulation parameters. Validation results show PhoenixMR simulations are three orders of magnitude faster. There is also strong agreement between models. Conclusions: A novel MRI simulation platform called PhoenixMR has been introduced. This research tool is designed to be usable by physicists and engineers interested in performing MRI simulations. Examples are shown demonstrating the accuracy, flexibility, and usability of PhoenixMR in several key areas of MRI simulation. [ABSTRACT FROM AUTHOR]

This document discusses the development of quantitative magnetic resonance imaging (qMRI) for objective tissue characterization in medical diagnosis and research. The article highlights the challenges of qMRI, such as motion artifacts and confounding effects, and explores recent advancements in hardware and software that have improved the accuracy and efficiency of body qMRI. The document also includes a collection of review articles and research papers that cover various aspects of qMRI, including the assessment of confounders, improvements in qMRI measurements, and novel post-processing methods. Overall, while there have been significant advancements in qMRI, further research and validation are needed to fully understand its potential in clinical applications. [Extracted from the article]

In this paper, we review the value of phantoms for body MRI in the context of their uses for quantitative MRI methods research, clinical trials, and clinical imaging. Certain uses of phantoms are common throughout the body MRI community, including measuring bias, assessing reproducibility, and training. In addition to these uses, phantoms in body MRI methods research are used for novel methods development and the design of motion compensation and mitigation techniques. For clinical trials, phantoms are an essential part of quality management strategies, facilitating the conduct of ethically sound, reliable, and regulatorily compliant clinical research of both novel MRI methods and therapeutic agents. In the clinic, phantoms are used for development of protocols, mitigation of cost, quality control, and radiotherapy. We briefly review phantoms developed for quantitative body MRI, and finally, we review open questions regarding the most effective use of a phantom for body MRI. [ABSTRACT FROM AUTHOR]

Aim: When patients receive radiation therapy for breast cancer, they need to take off their underwear to avoid build-up effects. However, it is a mental burden for female patients to take off their underwear at every fraction of radiation therapy. The purpose of this study was to investigate whether commercially available thin underwear can be worn during radiation therapy for breast cancer. Materials and methods: In this phantom study, we investigated whether commercially available underwear can be worn during radiation therapy for breast cancer using six thin non-disposable brassieres and one disposable paper brassiere. The dose increase rate (ΔD) was calculated by measuring skin doses with or without each brassiere. Results: The mean ΔD values of six non-disposable brassieres were 13.5% (9.0–21.8%), whereas that of disposable ones was 2.0%. Findings: Due to the risk of excessive radiation to the skin, wearing commercially available underwear is not recommended during radiation therapy for breast cancer, but a thin disposable paper brassiere may be safe to be used. [ABSTRACT FROM AUTHOR]

3D reconstruction is a useful tool for surgical planning and guidance. Supervised methods for disparity/depth estimation are the state of the art, with demonstrated performances far superior to all alternatives, such as self supervised and traditional geometric methods. However, supervised training requires large datasets, and in this field, data is lacking. In this paper, we investigate the learning of structured light projections to enhance the development of disparity estimation networks. Improving supervised learning on small datasets without needing to collect extra data. We first show that it is possible to learn the projection of structured light on a scene. Secondly, we show that the joint training of structured light and disparity, using a multi-task learning (MTL) framework, improves the learning of disparity. Our MTL setup outperformed the single task learning (STL) network in every validation test. Notably, in the generalisation test, the STL error was 1.4 times worse than that of the best MTL performance. A dataset containing stereoscopic images, disparity maps and structured light projections on medical phantoms and ex vivo tissue was created for evaluation together with virtual scenes. This dataset will be made publicly available in the future. [ABSTRACT FROM AUTHOR]

Radiation induced oral mucositis is a common side effect of radiation therapy in cancer patients. Many oral imaging techniques are available to assess the severity of oral mucositis and complement the subjective visual assessment. Non-contact commercial near-infrared (NIR) devices to evaluate oral mucositis currently are not available. NIR fluorescence imaging has been used, but it is an invasive technique involving injection of a contrast agent prior to imaging. Our objective was to develop and evaluate a non-invasive intraoral NIR probe, that can be used with minimal contact to the mouth during imaging. The probe was designed, and 3D printed as a hand-held device consisting of inter-changeable NIR light emitting diodes (LEDs) (680, 810, 830 nm) and an NIR-sensitive camera, both connected to a raspberry pi (a mini programmable computer) for remote operation of the device. The ability of the probe to perform non-contact imaging, detect NIR signals and penetrate beyond the scattering tissue surface was tested via phantom studies. The hand-held NIR probe could image the mouth without contacting the inside of the mouth 87% of the times it was used. It can detect NIR light and from beneath the surface of the oral tissue, demonstrating its potential for future assessment of oral mucositis. [ABSTRACT FROM AUTHOR]

Purpose: The advent of three‐dimensional breast imaging systems such as digital breast tomosynthesis (DBT) has great promise for improving the detection and diagnosis of breast cancer. With these new technologies comes an essential need for testing methods to assess the resultant image quality. Although randomized clinical trials are the gold standard for assessing image quality, phantom‐based studies can provide a simpler and less burdensome approach. In this work, a complete framework is presented for task‐based evaluation of microcalcification (MCs) detection performance for DBT imaging systems. Methods: The framework consists of three parts. The first part is a realistic anthropomorphic physical breast phantom created through inkjet printing, with parchment paper and iodine‐doped ink. The second is a method for inserting realistic MCs fabricated from calcium hydroxyapatite. The reproducibility and stability of the phantom materials were investigated through multiple samples of parchment and ink over 6 months. The final part is an analysis using a four‐alternative forced choice (4AFC) reader study. To demonstrate the framework, a task‐based 4AFC study was conducted using a clinical system to compare performance from DBT, synthetic mammography (SM), and full‐field digital mammography (FFDM). Nine human observers read images containing MC clusters imaged with all three modalities and tried to correctly locate the MCs. The proportion correct (PC) was measured as the number of correctly detected clusters out of all trials. Results: Overall, readers scored the highest with FFDM, (PC = 0.95 ± 0.03) then DBT (0.85 ± 0.04), and finally SM (0.44 ± 0.06). For the parchment and ink samples, the linear attenuation properties were very stable over 6 months. In addition, little difference was found between the various parchment and ink samples, indicating good reproducibility. Conclusions: This framework presents a promising methodology for evaluating diagnostic task performance of clinical breast DBT systems. [ABSTRACT FROM AUTHOR]