Imaging Mapping Research Articles

Quantitative muscle MRI in sporadic inclusion body myositis (sIBM): A prospective cohort study.

Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM. Longitudinal assessment of qMRI in sIBM patients. We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age- and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1), and radial diffusivity (RD) were analysed. Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA (p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed (p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles (r≤-0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (-0.04 10-3mm2/s), λ1 (-0.05 10-3mm2/s), and RD (-0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients (p≤0.001). FA showed no significant change (p = 0.242). qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations.

A retrospective evaluation of the potential of ChatGPT in the accurate diagnosis of acute stroke.

Stroke is a neurological emergency requiring rapid, accurate diagnosis to prevent severe consequences. Early diagnosis is crucial for reducing morbidity and mortality. Artificial intelligence (AI) diagnosis support tools, such as Chat Generative Pre-trained Transformer (ChatGPT), offer rapid diagnostic advantages. This study assesses ChatGPT's accuracy in interpreting diffusion-weighted imaging (DWI) for acute stroke diagnosis. A retrospective analysis was conducted to identify the presence of stroke using DWI and apparent diffusion coefficient (ADC) map images. Patients aged >18 years who exhibited diffusion restriction and had a clinically explainable condition were included in the study. Patients with artifacts that affected image homogeneity, accuracy, and clarity, as well as those who had undergone previous surgery or had a history of stroke, were excluded from the study. ChatGPT was asked four consecutive questions regarding the identification of the magnetic resonance imaging (MRI) sequence, the demonstration of diffusion restriction on the ADC map after sequence recognition, and the identification of hemispheres and specific lobes. Each question was repeated 10 times to ensure consistency. Senior radiologists subsequently verified the accuracy of ChatGPT's responses, classifying them as either correct or incorrect. We assumed a response to be incorrect if it was partially correct or suggested multiple answers. These responses were systematically recorded. We also recorded non-responses from ChatGPT-4V when it failed to provide an answer to a query. We assessed ChatGPT-4V's performance by calculating the number and percentage of correct responses, incorrect responses, and non-responses across all images and questions, a metric known as "accuracy." ChatGPT-4V was considered successful if it answered ≥80% of the examples correctly. A total of 530 diffusion MRI, of which 266 were stroke images and 264 were normal, were evaluated in the study. For the initial query identifying MRI sequence type, ChatGPT-4V's accuracy was 88.3% for stroke and 90.1% for normal images. For detecting diffusion restriction, ChatGPT-4V had an accuracy of 79.5% for stroke images, with a 15% false positive rate for normal images. Regarding identifying the brain or cerebellar hemisphere involved, ChatGPT-4V correctly identified the hemisphere in 26.2% of stroke images. For identifying the specific brain lobe or cerebellar area affected, ChatGPT-4V had a 20.4% accuracy for stroke images. The diagnostic sensitivity of ChatGPT-4V in acute stroke was found to be 79.57%, with a specificity of 84.87%, a positive predictive value of 83.86%, a negative predictive value of 80.80%, and a diagnostic odds ratio of 21.86. Despite limitations, ChatGPT shows potential as a supportive tool for healthcare professionals in interpreting diffusion examinations in stroke cases, where timely diagnosis is critical. ChatGPT can play an important role in various aspects of stroke cases, such as risk assessment, early diagnosis, and treatment planning.

Magnetic Resonance Imaging Biomarkers of Muscle.

This review is focused on the current status of quantitative MRI (qMRI) of skeletal muscle. The first section covers the techniques of qMRI in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1-weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, and diffusion tensor imaging to emerging qMRI features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMRI of muscle; the intent is to demonstrate the utility of qMRI in different disease states of the muscle rather than a complete comprehensive survey.

Evaluating the Impact of Digital Mapping and 3D Imaging Technologies on the Restoration of Historical Sites in Southeast Asia

The preservation of cultural heritage sites is undergoing a transformation, propelled by advancements in digital and 3D technologies. This paper explores the integration and impact of such technologies, including digital mapping, 3D imaging, Artificial Intelligence (AI), and the Internet of Things (IoT), on the conservation of historical sites. By providing detailed case studies from Southeast Asia, this study examines the accuracy improvements, enhanced visualization capabilities, and increased public engagement facilitated by these technologies. It also addresses the technical, financial, and training challenges associated with their implementation. Furthermore, the paper discusses the potential of emerging technologies to revolutionize heritage conservation and predicts future trends in the field. The findings suggest that while there are significant benefits to the adoption of these technologies, careful consideration is needed to overcome the associated challenges and ensure sustainable integration into conservation practices.

Quantitative assessment of gadolinium deposition in dentate nuclei with MR fingerprinting

Gadolinium deposition in the dentate nucleus (DN) has been evaluated by T1-weighted imaging (T1WI) and T1 (R1) mapping, but not MR fingerprinting (MRF). This study investigated associations between T1 and T2 values of DN and gadolinium-based contrast agents (GBCAs) using 2-dimensional MRF. This study included 101 patients. Region of interest analysis was performed for T1 and T2 values of DN on MRF (T1-MRF, T2-MRF) and T1-weighted images (T1WI ratio). T1 and T2 ratios compared to normal cerebellar white matter (T1-MRF ratio, T2-MRF ratio) were calculated. The type of previous GBCA was confirmed in 79 patients, and linear regressions were performed between T1, T2 values and number of GBCAs. Good correlations were observed between T1-MRF and T1WI ratio (ρ=-0.69, P<0.001) and between T1-MRF ratio and T1WI ratio (ρ=-0.76, P<0.001). Mild correlations were observed between T2-MRF and T1WI ratio (ρ=-0.32, P<0.001) and between T2-MRF ratio and T1WI ratio (ρ=-0.44, P<0.001). The number of linear-type GBCAs was associated with T1-MRF (β=-0.62, P<0.001) and T1-MRF ratio (β=-0.54, P<0.001) in univariate linear regression analyses, and with T1-MRF (β=-0.61, P<0.001) and T1-MRF ratio (β=-0.53, P<0.001) in multivariate analysis. The number of linear-type GBCAs was associated with T2-MRF (β=-0.30, P<0.001) and T2-MRF ratio (β=-0.29, P<0.001) in univariate analyses, and with T2-MRF (β=-0.31, P<0.001) and T2-MRF ratio (β=-0.32, P<0.001) in multivariate analyses. No associations were observed between number of macrocyclic GBCAs and T1-MRF (ratio) or T2-MRF (ratio). The number of linear-type GBCA administrations was associated with lower T1 and T2 values (ratios) in DN.

Augmented Reality-Based Chronic Wound Healing Assessment Using 3D Stereoscopic Imaging and Self-Organizing Maps

Background: Chronic wounds (CW) present significant public health challenges, impacting individuals' well-being and daily activities. Traditional wound measurement methods, such as the ruler technique, are time-consuming, imprecise, and pose infection risks. Advances in wound care technology, including artificial intelligence (AI) and augmented reality (AR), have improved wound healing (WH) assessment accuracy and enhanced clinician-patient communication. Methods: This study developed a novel CW evaluation device combining AR and a stereoscopic camera system. The device captures images using two Leopard Imaging LI-OV580 stereo cameras and a pico-projector to create a 3D wound model. The system calculates the wound area by processing stereoscopic images, utilizing structured-from-motion techniques and convolutional neural networks (CNNs). Additionally, the device measures epipolar and projection errors (PE) during AR-based wound evaluation. A Self-Organizing Map (SOM) was employed to refine the 3D reconstruction of the wound. Results: The AR-PE analysis demonstrated the device's accuracy, with the lowest PE recorded at 20 cm from the wound area. The projection error increased as the measurement distance moved toward the edges of the wound. The average epipolar error (EE) was 0.46 pixels, indicating high precision in stereoscopic measurements. Conclusion: The study introduced a non-invasive CW evaluation device that improves wound assessment accuracy and clinician-patient interaction. By utilizing 3D wound modeling and AR, the system enables more effective communication and progress tracking during WH. The results suggest this technology could enhance CW management, offering a reliable alternative to traditional methods.

Facile synthesis, multimode and tunable luminescence, and multifunctional applications of rare earth ions activated lead-free double perovskite crystals

Lead-free double perovskites have gained recognition as top luminescent materials due to their environmental friendliness, high chemical stability, structural adjustability, and excellent photoelectric properties. However, the poor modulation of emission restricts their applications, and it is highly desirable to explore stable and efficient double perovskites with multimode luminescence and adjustable spectra for multifunctional photoelectric applications. Herein, the rare earth ions Ln3+ (Er3+ and Ho3+) doped Cs2NaYCl6:Sb3+ crystals were synthesized by a simple solvothermal route. The X-ray diffraction pattern (XRD), energy-dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and elemental mapping images demonstrate that the Sb3+, Er3+, and Ho3+ ions have been homogeneously incorporated into the Cs2NaYCl6 crystals. As anticipated, the emission spectra of Cs2NaYCl6:Sb3+/Ln3+ are composed of two bands. One broad blue band derives from self-trapped exciton (STE) in [SbCl6]3− octahedra while another group of emission peaks stems from the f-f transitions of Ln3+ ions. The emission colors of Cs2NaYCl6:Sb3+/Ln3+ phosphors can be tuned in a wide range by modulating the doping concentrations of Ln3+ ions. The efficient energy transfer from STE to Ln3+ is the key point to achieving the efficient and tunable emissions Cs2NaYCl6:Sb3+/Ln3+ samples. Interestingly, Cs2NaYCl6:Sb3+/Ln3+ can also exhibit characteristic up-conversion luminescence of Ln3+ under near-infrared (NIR) excitation besides the down-conversion luminescence, revealing that the materials may have potential applicability in multimode anti-counterfeiting and information encryption applications. Furthermore, the light emitting diodes (LEDs) assembled by Cs2NaYCl6:Sb3+ and Cs2NaYCl6:Sb3+/Ln3+ phosphors display dazzling blue, green, and red emissions under a forward bias current, which indicates that the as-obtained double perovskites materials may have great potential in solid-state lighting and optoelectronic devices.

XUV-beamline for photoelectron imaging spectroscopy with shaped pulses.

We introduce an extreme ultraviolet (XUV)-beamline designed for the time-resolved investigation and coherent control of attosecond (as) electron dynamics in atoms and molecules by polarization-shaped as-laser pulses. Shaped as-pulses are generated through high-harmonic generation (HHG) of tailored white-light supercontinua (WLS) in noble gases. The interaction of shaped as-pulses with the sample is studied using velocity map imaging (VMI) techniques to achieve the differential detection of photoelectron wave packets. The instrument consists of the WLS-beamline, which includes a hollow-core fiber compressor and a home-built 4f polarization pulse shaper, and the high-vacuum XUV-beamline, which combines an HHG-stage and a versatile multi-experiment vacuum chamber equipped with a home-built VMI spectrometer. The VMI spectrometer allows the detection of photoelectron wave packets from both the multiphoton ionization (MPI) of atomic or molecular samples by the tailored WLS-pulses and the single-photon ionization (SPI) by the shaped XUV-pulses. To characterize the VMI spectrometer, we studied the MPI of xenon atoms by linearly polarized WLS pulses. To validate the interplay of these components, we conducted experiments on the SPI of xenon atoms with linearly polarized XUV-pulses. Our results include the reconstruction of the 3D photoelectron momentum distribution (PMD) and initial findings on the coherent control of the PMD by tuning the spectrum of the XUV-pulses with the spectral phase of the WLS. Our results demonstrate the performance of the entire instrument for HHG-based photoelectron imaging spectroscopy with prototypical shaped pulses. Perspectively, we will employ polarization-tailored WLS-pulses to generate polarization-shaped as-pulses.

Evaluation of Preoperative Low-flow Areas in STA-MCA Bypass Surgery Using Vascular Fusion Map Image.

The superficial temporal artery-middle cerebral artery (STA-MCA) bypass surgery requires an anastomosis of the STA to an MCA with diminished blood flow. However, identifying the precise location of the MCA with reduced flow preoperatively is challenging as it often remains nonvisualized. To address this issue, we developed a novel technique, the area target bypass (ATB) method, to infer the location of the responsible vessel for low-flow areas. The cornerstone of the ATB method lies in the utilization of the vascular fusion map (VFM). The VFM integrates 3D perfusion and 3D vascular images, enabling simultaneous evaluation of cerebral surface vessels and regions with reduced blood flow. This study aimed to assess the efficacy of the STA-MCA bypass surgery adopting the ATB method. Between August 2022 and March 2023, we conducted eight STA-MCA bypass surgeries using the ATB method. For each case, the VFM was generated using the MTT and DLY parameters, and blood flow improvement was evaluated based on the VFM score, determined by an average score from seven experts. In all cases, the target vessel was identified either preoperatively or during craniotomy, with postoperative patency of the STA-MCA bypass confirmed. Out of the eight cases, seven demonstrated improved blood flow with a VFM score exceeding 1. No complications were reported. The introduction of the ATB method has proven its potential in accurately pinpointing optimal anastomosis sites.

Reliability of quantitative magnetic susceptibility imaging metrics for cerebral cortex and major subcortical structures.

Susceptibility estimates derived from quantitative susceptibility mapping (QSM) images for the cerebral cortex and major subcortical structures are variably reported in brain magnetic resonance imaging (MRI) studies, as average of all ( ), absolute ( ), or positive- ( ) and negative-only ( ) susceptibility values using a region of interest (ROI) approach. This pilot study presents a reliability analysis of currently used ROI-QSM metrics and an alternative ROI-based approach to obtain voxel-weighted ROI-QSM metrics ( and ). Ten healthy subjects underwent repeated (test-retest) 3-dimensional multi-echo gradient-echo (3DMEGE) 3 Tesla MRI measurements. Complex-valued 3DMEGE images were acquired and reconstructed with slice thicknesses of 1 and 2mm (3DMEGE1, 3DMEGE2) along with 3DT1-weighted isometric (voxel 1 mm3) images for independent registration and ROI segmentation. Agreement, consistency, and reproducibility of ROI-QSM metrics were assessed through Bland-Altman analysis, intraclass correlation coefficient, and interscan and intersubject coefficient of variation (CoV). All ROI-QSM metrics exhibited good to excellent consistency and test-retest agreement with no proportional bias. Interscan CoV was higher for in comparison to the other metrics where it was below 15%, in both 3DMEGE1 and 3DMEGE2 datasets. Intersubject CoV for and exceeded 50% in all ROIs. Among the evaluated ROI-QSM metrics, and estimates were less reliable, whereas separating positive and negative values (using ) improved the reproducibility within, and the comparability between, subjects, even when reducing the slice thickness. These preliminary findings may offer valuable insights toward standardizing ROI-QSM metrics across different patient cohorts and imaging settings in future clinical MRI studies.

Combined use of multi-source satellite imagery and deep learning for automated mapping of glacial lakes in the Bhutan Himalaya

Himalayan glacial lakes have been rapidly developing and expanding in recent decades under climate change and glacier mass loss. These growing glacial lakes can produce glacial lake outburst floods (GLOFs) events with far-reaching and devastating consequences. However, the latest spatial distribution and temporal evolution of the Himalayan glacial lakes is not timely updated due to the inaccessibility of high mountain areas and the lack of an effective automated mapping method that can leverage the availability of wide-ranging remote sensing data. To frequently update glacial lake inventory in GLOF-vulnerable regions, we developed the state-of-the-art glacial lake mapping approaches based on deep learning technique and multi-source remote sensing imagery. DeepLabv3+, an advanced semantic segmentation algorithm, was trained to delineate glacial lakes with areas larger than 0.005 km2 from multi-source imagery and their derivatives, including PlanetScope red-green-blue (RGB), PlanetScope-derived Normalized Difference Water Index (NDWI), Sentinel-2 RGB, Sentinel-2-derived NDWI, Sentinel-1 Synthetic Aperture Radar (SAR), and Landsat-8 RGB images. The well-trained deep learning models achieved high mapping accuracy in the northern Bhutan test region, with the F1 score varying from 0.74 (Sentinel-1) to 0.91 (Planet-RGB) among the six types of images. We applied the well-trained models to automatically map the glacial lakes from multi-source satellite imagery. After manually cataloging the mapping results, we compiled a glacial lake inventory for the Bhutan Himalaya in 2021 that includes 2563 glacial lakes with a total area of 153.85 ± 9.33 km2. Our results demonstrated the mapping capability of deep learning on multiple satellite imagery, the key roles of PlanetScope optical images for accurate glacial lake mapping, and the essential supplementary usage of SAR images and NDWI images to complement the glacial lake inventory over Bhutan Himalaya. This study provides an advanced and transferable workflow for inventorying glacial lakes from multi-source satellite imagery, as well as provides a high-quality and comprehensive glacial lake inventory for outburst flood studies.

Multiobjective sparse unmixing based hyperspectral change detection

Hyperspectral unmixing can provide the composition of ground objects, while change detection can identify the changes of the same region over time. Therefore, unmixing based hyperspectral change detection can investigate changes in a subpixel-level. It can provide not only whether the change happens or not but also how to change. This paper will gradually establish an unconstrained sparse unmixing based change detection model and design a multiobjective optimization sparse unmixing approach (termed MoSU-CD) to solve it for more subpixel-level change details. Compared with the existing sparse unmixing based change detection approaches, MoSU-CD directly unmixes the difference map of multi-temporal images rather than multi-temporal images themselves respectively. Then it explores the change details of one substance in each pixel based on the unmixing results, i.e., endmembers and abundances. In addition, in order to improve the change detection accuracy, an ensemble decision strategy is designed for the Pareto optimal solutions obtained by multiobjective optimization method. Based on this strategy, the subpixel-level changes can be aggregated to generate an aggressive pixel-level change map. The experimental results on synthetic and real data sets demonstrate that the proposed MoSU-CD not only outperforms the benchmark and state-of-art approaches in terms of pixel-level change detection but also provides additional subpixel-level change information.

Evaluation of mining landscape changes with development landscape metrics in the Ostrava-Karviná Mining District (Czech Republic).

The study presents an analysis of changes in the landscape of the Ostrava-Karviná Mining District (in the Czech Republic) covering the period of more than 170years. In the area of interest affected by underground coal mining, both areas affected by changes and land cover preserving areas were identified in the study. A detailed assessment of the landscape changes was enabled by using landscape metrics and indices, namely the development index and total landscape change index. The underlying data were obtained from maps of stable cadastre (from the year 1836) and aerial images of the years 1947, 1971, and 2009. Visual photointerpretation of aerial images and interpretation of the maps of stable cadastre made it possible to create land cover maps according to CORINE Land Cover categories. Obtained information on the representation of individual land cover categories were used to identify and to analyze changes in the landscape affected by hard coal mining.

MULTIFRACTAL ANALYSIS OF POLARIZATION MAPS OF ELLIPTICITY OF MICROSCOPIC IMAGES OF BLOOD SMEARS AND DIFFERENTIAL DIAGNOSIS OF THYROID GLAND PATHOLOGY

Among the numerous biomedical diagnostic applications of the soft matter structure,Mueller- matrix polarimetry of the optical anisotropy of biological tissues occupies animportant place. Various Mueller- matrix polarimetry systems have been developed toimplement the diagnostic tasks.The aim of the study – to conduct a comparative analysis of the effectiveness of themultifractal processing method of polarization ellipticity maps of digital microscopicimages of supramolecular protein networks of polycrystalline blood smears in orderto determine new objective criteria (markers) of digital laser histological differentialdiagnosis of the thyroid gland pathology.Material and methods. Four observation groups were formed: 1. Control group – healthydonors (51 people). 2. Patients with nodular goiter (51 patients). 3. Patients with autoimmunethyroiditis (51 patients). 4. Patients with papillary cancer (51 patients). A comparative analysisof the effectiveness of the statistical and multifractal processing methods of polarizationellipticity maps of digital microscopic images of supramolecular protein networks ofpolycrystalline blood smears was carried out in order to determine new objective criteria(markers) of digital laser histological differential diagnosis of the thyroid pathology. Results. A comprehensive statistical and multifractal analysis of polarization ellipticitymaps of experimental blood samples of donors and patients with nodular goiter,autoimmune thyroiditis, and papillary cancer was performed. Objective statistical andmultifractal markers for differential diagnosis of the thyroid gland pathology weredetermined. An excellent level (~96 %-98 %) of the balanced accuracy of the multifractalanalysis method of polarization maps of blood for minimally invasive differentiation ofpathological conditions has been demonstrated.Conclusions. 1. The most optimal statistical markers of the method of mapping ellipticitymaps of polarization of digital microscopic images of blood smears were found to bethe most optimal, and a good diagnostic capacity of diagnosis (~87.3 %-88.3 %) anda satisfactory level (~78.4 %-81.4 %) of differentiation of thyroid pathology wereestablished. 2. Multifractal markers of the mapping ellipticity maps method of polarizationof digital microscopic images of blood smears were found to be the most optimal and anexcellent level (~96 %-98 %) of the balanced accuracy of differential diagnosis of thethyroid gland pathologies was established.

Experimental Replacement of Zircon by Melt‐Mediated Coupled Dissolution‐Precipitation Causes Dispersion in U–Pb Ages

ABSTRACTZircon geochronology provides critical information on the rates and durations of geological processes and enables researchers to explore deep time. However, some zircon datasets show a continuum of concordant ages (‘smear’) without well‐defined age populations. These age smears are typically interpreted to represent variable loss of radiogenic Pb or protracted geological events lasting tens of millions of years. Coupled dissolution‐precipitation replacement of zircon has been suggested as one process that may produce these complex age datasets. Here, we react fragments of the well characterised Mud Tank zircon standard with natural intermediate and mafic melts (0.9 GPa, 1100–1180°C) to test if short‐term exposure to a melt can modify the geochronological patterns of zircon. Our observations show that within a short duration (18 h to 3.5 days), most Mud Tank zircon fragments display microstructural and/or chemical evidence for modification by dissolution at fragment boundaries along with partial replacement by coupled dissolution‐precipitation processes. The replaced zircon domains have U–Pb ages that smear over one hundred million years, between 764–647 Ma, illustrating variable mobility and redistribution of the U and Pb isotopes. Our experiments demonstrate that zircon modified by coupled dissolution‐precipitation replacement may not faithfully record the age or duration of geological events and that investigation of zircon microstructure in high‐resolution backscattered electron, cathodoluminescence imaging and/or Raman mapping is needed to better understand complex zircon geochronological datasets.

Evaluation of Right Ventricular Myocardial Properties Using Systolic Myocardial T1 Mapping.

Introduction Myocardial properties can be quantitatively evaluated using myocardial native T1 values (nT1) obtained using cardiac magnetic resonance imaging (CMR). In terms of myocardial wall thickness, the left ventricular nT1 is easy to measure, but the right ventricular nT1 is difficult. Patients with congenital heart disease often develop right ventricular overload. If right ventricular nT1 can be measured consistently, inflammation and fibrosis of the right ventricular myocardium can be quantitatively evaluated. We aimed to determine whether T1 mapping during systole can be used to evaluate right ventricular myocardial properties. Methods T1 mapping was performed at diastole and systole. Systolic T1 mapping was calculated from diastolic T1 mapping and cine images. The myocardial properties of both ventricles were evaluated in 13 healthy volunteers (21-26 years old) and 12 patients with right ventricular overload (12-41 years old) who underwent CMR examination at our hospital. Results From the analysis of left ventricular nT1, we found that nT1 did not change significantly during the cardiac cycle. However, right ventricular nT1 changed between diastole and systole because the right ventricle is affected by blood. Although there was no difference in right ventricular diastolic nT1 between the patients and volunteers (1,346.8 vs. 1,347.6 ms, p = 0.852), the right ventricular systolic nT1 was significantly higher in patients than in volunteers (1,312.7 vs. 1,233.8 ms, p = 0.002). This indicates that right ventricular myocardial damage occurs in patients with right ventricular overload. Conclusion Systolic right ventricular myocardial T1 mapping allows assessment of right ventricular myocardial properties. The right ventricular myocardial systolic nT1 is useful for evaluating myocardial damage due to right ventricular stress and myocardial injury. Measuring right ventricular nT1 may allow consideration of early therapeutic intervention.

Experimental Comparison of Two 6D Pose Estimation Algorithms in Robotic Fruit-Picking Tasks

This paper presents an experimental comparison between two existing methods representative of two categories of 6D pose estimation algorithms nowadays commonly used in the robotics community. The first category includes purely deep learning methods, while the second one includes hybrid approaches combining learning pipelines and geometric reasoning. The hybrid method considered in this paper is a pipeline of an instance-level deep neural network based on RGB data only and a geometric pose refinement algorithm based on the availability of the depth map and the CAD model of the target object. Such a method can handle objects whose dimensions differ from those of the CAD. The pure learning method considered in this comparison is DenseFusion, a consolidated state-of-the-art pose estimation algorithm selected because it uses the same input data, namely, RGB image and depth map. The comparison is carried out by testing the success rate of fresh food pick-and-place operations. The fruit-picking scenario has been selected for the comparison because it is challenging due to the high variability of object instances in appearance and dimensions. The experiments carried out with apples and limes show that the hybrid method outperforms the pure learning one in terms of accuracy, thus allowing the pick-and-place operation of fruits with a higher success rate. An extensive discussion is also presented to help the robotics community select the category of 6D pose estimation algorithms most suitable to the specific application.

Conversion of images of 3D friction maps to study the coupling between coefficient of friction, velocity and contact temperature of the disc brake

The coefficient of friction during braking is not constant. Determining its variability requires measurements in real conditions. This paper presents a methodology of conversion of the measured time profiles of the sliding velocity Veq, contact temperature T, and coefficient of friction f, into analytical formulation of two variables z = f(x,y). This was executed in the following steps: 1) creating a three-column table Veq, T, f from experimental measurements; 2) interpolation using Kriging; 3) creating a contour map of the coefficient of friction dependent on the sliding velocity and temperature, 4) import of a grey scale image of the friction map into the finite element (FE) software, and 5) definition of a function z = f(x,y). The studies were carried out for five composite organic friction materials and cast-iron brake disc of a railway vehicle. The developed five friction maps for each friction pair were based the data from the full-scale bench tests during braking from the initial vehicle velocity of 80 kmh−1, 120 kmh−1, 140 kmh−1, 160 kmh−1, 200 kmh−1 to a stop. In the second part of the study the initial-value problem for the equation of motion combined with the heat conduction problem were formulated and solved numerically using special functionalities of the FE software, e.g. Deformed Geometry, Mathematics. Changes in the vehicle velocity and time profiles of the coefficient of friction were determined from the solution of the coupled thermal problem. The computational FE model was verified by comparing the measured and calculated changes in the vehicle velocity, coefficient of friction and evolutions of the brake disc temperature during single braking. The maximum calculated temperature 1 mm under the contact surface of the brake disc, during braking from initial vehicle velocity of 80 kmh−1, was obtained for the base friction material and was equal to T1,3,5Num.= 72 °C. The corresponding experimental value was T1-6Exp.= 66.1 °C. When braking from 140 kmh−1, for the same material it was T1,3,5Num.= 129.7 °C and T1-6Exp.= 130.7 °C. The obtained differences in braking times calculated and measured did not exceed 1.7 %. The corresponding temperature differences of the disc at the stopping time were lower than 5.5 %.

Multi-Stage Feature Fusion of Multispectral and SAR Satellite Images for Seasonal Crop-Type Mapping at Regional Scale Using an Adapted 3D U-Net Model

Multi-Stage Feature Fusion of Multispectral and SAR Satellite Images for Seasonal Crop-Type Mapping at Regional Scale Using an Adapted 3D U-Net Model

Efficient removal of fluoride from water by CaO/Ca12Al14O33/Ca5Al6O14 composites: Performance and mechanism

CaO/Ca12Al14O33/Ca5Al6O14 composites were synthesized through calcination of Ca-Al layered double hydroxides (CaAl-LDHs). The structures of the CaAl-LDHs and the composites were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and nitrogen adsorption–desorption isotherms. Batch experiments were carried out to study the influence of various experimental parameters such as initial fluoride concentration, contact time, pH and the coexisting anions on the adsorption of fluoride. The fluoride adsorption follows the Freundlich isotherm model. With the World Health Organization (WHO) guideline of 1.5 mg L−1, the adsorption capacity was 52.78 mg g−1. The kinetic data were fitted to the pseudo-second-order model. The change of pH (3–10) has almost no influence on the fluoride removal. High concentration of the coexisted sulfate, carbonate and phosphate anions slightly inhibited the fluoride removal. The fluoride removal mechanism study suggested that CaO transformed into CaF2 after fluoride adsorption, which play key roles in fluoride removal. The hydrolysis of Ca12Al14O33 and Ca5Al6O14 resulted the formation of Ca3Al2(OH)12. Fluoride anions participated in this hydrolysis process and resulted in the formation of Ca3Al2(OH)12-xFx, which was revealed by XRD, X-ray photoelectron spectroscopy analysis (XPS) and SEM elemental mapping images.