Low Frame Research Articles

Application of Dynamic Mode Decomposition to Study Temporal Flow Behavior in a Saccular Aneurysm.

Aneurysms are abnormal expansion of weakened blood vessels which can cause mortality or long-term disability upon rupture. Several studies have shown that inflow conditions spatially and temporally influence aneurysm flow behavior. The objective of this investigation is to identify impact of inflow conditions on spatio-temporal flow behavior in an aneurysm using dynamic mode decomposition (DMD). For this purpose, low-frame rate velocity field measurements are performed in an idealized aneurysm model using particle image velocimetry (PIV). The inflow conditions are precisely controlled using a ViVitro SuperPump system where nondimensional fluid parameters such as peak Reynolds number (Rep) and Womersely number (α) are varied from 50-270 and 2-5, respectively. The results show the ability of DMD to identify the spatial flow structures and their frequency content. Furthermore, DMD captured the impact of inflow conditions, and change in mode shapes, amplitudes, frequency, and growth rate information is observed. The DMD low-order flow reconstruction also showed the complex interplay of flow features for each inflow scenario. Furthermore, the low-order reconstruction results provided a mathematical description of the flow behavior in the aneurysm which captured the vortex formation, evolution, and convection in detail. These results indicated that the vortical structure behavior varied with the change in α while its strength and presence of secondary structures are influenced by the change in Rep.

Terahertz rainbow spectrum imager on reflective metasurfaces

The terahertz imagers that have already developed are usually with low frame rate and high cost, making them ineffective for moving target detection and fast imaging. Here, we experimentally report a high-frame-rate, high-resolution and low-cost real-aperture imager developed by combining the terahertz rainbow spectrum manipulation metasurface and quasi-optical method. As a wideband THz signal incidents on such metasurface (called as THz virtual prism), terahertz rainbow spectrum can be formed in one dimension just like a light beam passing through an optical prism, and complete real-aperture scanning imaging within 100 microseconds. By using high-speed displacement platform to realize another dimensional scanning, this imager will easily achieve high-frame-rate and high-resolution imaging with simple algorithm. The feasibility of this new THz imager was verified by imaging Siemens star and concealed targets, respectively. The results show that this imager has important potential applications in fields such as THz remote sensing, imaging radar, body scanner, etc.

New Low-Frame-Rate Compensating Pixel Circuit Based on Low-Temperature Poly-Si and Oxide TFTs for High-Pixel-Density Portable AMOLED Displays.

A new low-frame-rate active-matrix organic light-emitting diode (AMOLED) pixel circuit with low-temperature poly-Si and oxide (LTPO) thin-film transistors (TFTs) for portable displays with high pixel density is reported. The proposed pixel circuit has the excellent ability to compensate for the threshold voltage variation of the driving TFT (ΔVTH_DTFT). By the results of simulation based on a fabricated LTPS TFT and a-IZTO TFT, we found that the error rates of the OLED current were all lower than 2.71% over the range of input data voltages when ΔVTH_DTFT = ±0.33 V, and a low frame rate of 1 Hz could be achieved with no flicker phenomenon. Moreover, with only one capacitor and two signal lines in the pixel circuit, a high pixel density and narrow bezel are expected to be realized. We revealed that the proposed 7T1C pixel circuit with low driving voltage and low frame rate is suitable for portable displays.

Shunt currents in vanadium redox flow batteries – a parametric and optimization study

Shunt currents can hinder the performance and reduce the lifespan of redox flow batteries. This work focuses on finding the best approach to mitigate the shunt currents in vanadium redox flow batteries. A 2-D dynamic phenomenological model was used to compute the shunt currents as a function of the design and operating conditions of a stack with 6 cells and 16 cm2 active area, operated at 80 mA cm−2. In parallel, an equivalent circuit model was used to compute the same shunt currents but with a far smaller computing time. Finally, an artificial intelligence-based software was used to obtain a simple mathematical correlation that best fit the simulated shunt currents, as a function of the external resistances (manifold and flow frame channels, from 0.08 to 2621 Ω), operating current (from 4 to 512 A) and number of cells (from 5 to 40) in a stack. The correlation was then used to perform a sensitivity analysis to the previous parameters.The results show that the shunt currents decrease with the internal resistances (activation, ohmic and mass transport). Nonetheless, the external resistances have the greatest impact in the shunt currents, particularly the manifold electrical resistance. Based on these findings, a novel redox flow battery stack design (343 cm2 active area), with a high manifold resistance and a low flow frame channel resistance, is proposed to mitigate the shunt currents; cells with no electrochemical activity (dumping cells), evenly inserted into the stack, were considered to increase the manifold resistance. This new stack displays 23.6% lower shunt current losses, 33% lower pressure drop and 19% higher nominal power output at 80 mA cm−2 when compared with a conventional stack.

Enhanced Real-Time Intermediate Flow Estimation for Video Frame Interpolation

Recently, the demand for high-quality video content has rapidly been increasing, led by the development of network technology and the growth in video streaming platforms. In particular, displays with a high refresh rate, such as 120 Hz, have become popular. However, the visual quality is only enhanced if the video stream is produced at the same high frame rate. For the high quality, conventional videos with a low frame rate should be converted into a high frame rate in real time. This paper introduces a bidirectional intermediate flow estimation method for real-time video frame interpolation. A bidirectional intermediate optical flow is directly estimated to predict an accurate intermediate frame. For real-time processing, multiple frames are interpolated with a single intermediate optical flow and parts of the network are implemented in 16-bit floating-point precision. Perceptual loss is also applied to improve the cognitive performance of the interpolated frames. The experimental results showed a high prediction accuracy of 35.54 dB on the Vimeo90K triplet benchmark dataset. The interpolation speed of 84 fps was achieved for 480p resolution.

Label-free quantitative measurement of cardiovascular dynamics in a zebrafish embryo using frequency-comb-referenced-quantitative phase imaging.

.Significance: Real-time monitoring of the heart rate and blood flow is crucial for studying cardiovascular dysfunction, which leads to cardiovascular diseases.Aim: This study aims at in-depth understanding of high-speed cardiovascular dynamics in a zebrafish embryo model for various biomedical applications via frequency-comb-referenced quantitative phase imaging (FCR-QPI).Approach: Quantitative phase imaging (QPI) has emerged as a powerful technique in the field of biomedicine but has not been actively applied to the monitoring of circulatory/cardiovascular parameters, due to dynamic speckles and low frame rates. We demonstrate FCR-QPI to measure heart rate and blood flow in a zebrafish embryo. FCR-QPI utilizes a high-speed photodetector instead of a conventional camera, so it enables real-time monitoring of individual red blood cell (RBC) flow.Results: The average velocity of zebrafish’s RBCs was measured from 192.5 to at 24 to 28 hour-post-fertilization (hpf). In addition, the number of RBCs in a pulsatile blood flow was revealed to 16 cells/pulse at 48 hpf. The heart rates corresponded to 94 and 142 beats-per-minute at 24 and 48 hpf.Conclusions: This approach will newly enable in-depth understanding of the cardiovascular dynamics in the zebrafish model and possible usage for drug discovery applications in biomedicine.

Spatial‐temporal slowfast graph convolutional network for skeleton‐based action recognition

In skeleton-based action recognition, the graph convolutional network (GCN) has achieved great success. Modelling skeleton data in a suitable spatial-temporal way and designing the adjacency matrix are crucial aspects for GCN-based methods to capture joint relationships. In this study, we propose the spatial-temporal slowfast graph convolutional network (STSF-GCN) and design the adjacency matrices for the skeleton data graphs in STSF-GCN. STSF-GCN contains two pathways: (1) the fast pathway is in a high frame rate, and joints of adjacent frames are unified to build ‘small’ spatial-temporal graphs. A new spatial-temporal adjacency matrix is proposed for these ‘small’ spatial-temporal graphs. Ablation studies verify the effectiveness of the proposed adjacency matrix. (2) The slow pathway is in a low frame rate, and joints from all frames are unified to build one ‘big’ spatial-temporal graph. The adjacency matrix for the ‘big’ spatial-temporal graph is obtained by computing self-attention coefficients of each joint. Finally, outputs from two pathways are fused to predict the action category. STSF-GCN can efficiently capture both long-range and short-range spatial-temporal joint relationships. On three datasets for skeleton-based action recognition, STSF-GCN can achieve state-of-the-art performance with much less computational cost.

Importance of frame rate for the measurement of strain and synchrony in fetuses using speckle tracking echocardiography.

To assess the influence of frame rate settings on longitudinal strain (LS) and mechanical synchrony (SYN) values in Speckle Tracking Echocardiography (STE) of healthy fetuses. In this prospective study, we collected transversal or apical four-chamber-views of 121 healthy fetuses between 20 and 38weeks of gestation using three different frame rate (FR) settings (≥ 110, 100±10, 60±10 frames per second). We assessed the segmental and the global LS of both ventricles (2C) and of the left ventricle (LV) offline with QLab 10.8 (Philips Medical Systems, Andover, MA, USA). Inter- and intraventricular SYN were calculated as time difference in peak myocardial strain between the mid-segments of left and right ventricle (interventricular, 2C_Syn) and lateral wall and septum of the left ventricle (intraventricular, LV_Syn), respectively. In 84.3% STE was feasible at all three FR settings. The LS increased in both views at higher FRs to a statistically noticeable extent. SYN measurements and the absolute differences at patient level between the FR settings showed no statistically noticeable alterations. STE is feasible at low and high FR settings. SYN emerges to be a robust parameter for fetal STE as it is less affected by the FR. High FRs enable high temporal resolutions and thus an accurate examination of fetal hearts. Future research for the technical implementation of tailored fetal STE software is necessary for reliable clinical application.

Ultrasound microvasculature imaging with entropy-based radiality super-resolution (ERSR)

Objective: Microvasculature is highly relevant to the occurrence and development of pathologies such as cancer and diabetes. Ultrasound localization microscopy (ULM) has bypassed the diffraction limit and demonstrated its great potential to provide new imaging modality and establish new diagnostic criteria in clinical application. However, sparse microbubble distribution can be a significant bottleneck for improving temporal resolution, even for further clinical translation. Other important challenges for ULM to tackle in clinic also include high microbubble concentration and low frame rate. Approach: As part of the efforts to facilitate clinical translation, this paper focused on the low frame rate and the high microbubble distribution issue and proposed a new super-resolution imaging strategy called entropy-based radiality super-resolution (ERSR). The feasibility of ERSR is validated with simulations, phantom experiment and contrast-enhanced ultrasound scan of rabbit sciatic nerve with clinical accessible ultrasound system. Main results: ERSR can achieve 10 times improvement in spatial resolution compared to conventional ultrasound imaging, higher temporal resolution (∼10 times higher) and contrast-to-noise ratio under high-density microbubbles, compared with ULM under low-density microbubbles. Significance: We conclude ERSR could be a valuable imaging tool with high spatio-temporal resolution for clinical diagnosis and assessment of diseases potentially.

Ten-mega-pixel snapshot compressive imaging with a hybrid coded aperture

High-resolution images are widely used in our everyday life; however, high-speed video capture is more challenging due to the low frame rate of cameras working at the high-resolution mode. The main bottleneck lies in the low throughput of existing imaging systems. Toward this end, snapshot compressive imaging (SCI) was proposed as a promising solution to improve the throughput of imaging systems by compressive sampling and computational reconstruction. During acquisition, multiple high-speed images are encoded and collapsed to a single measurement. Then, algorithms are employed to retrieve the video frames from the coded snapshot. Recently developed plug-and-play algorithms made the SCI reconstruction possible in large-scale problems. However, the lack of high-resolution encoding systems still precludes SCI’s wide application. Thus, in this paper, we build, to the best of our knowledge, a novel hybrid coded aperture snapshot compressive imaging (HCA-SCI) system by incorporating a dynamic liquid crystal on silicon and a high-resolution lithography mask. We further implement a PnP reconstruction algorithm with cascaded denoisers for high-quality reconstruction. Based on the proposed HCA-SCI system and algorithm, we obtain a 10-mega-pixel SCI system to capture high-speed scenes, leading to a high throughput of 4.6 × 109 voxels per second. Both simulation and real-data experiments verify the feasibility and performance of our proposed HCA-SCI scheme.

Feasibility and Accuracy of a Fully Automated Right Ventricular Quantification Software With Three-Dimensional Echocardiography: Comparison With Cardiac Magnetic Resonance.

Background: A novel, fully automated right ventricular (RV) software for three-dimensional quantification of RV volumes and function was developed. The direct comparison of the software performance with cardiac magnetic resonance (CMR) was limited. Therefore, the aim of this study was to test the feasibility, accuracy, and reproducibility of a fully automated RV quantification software against CMR imaging as a reference.Methods: A total of 170 patients who underwent both CMR and three-dimensional echocardiography were enrolled. RV end-diastolic volume (RVEDV), RV end-systolic volume (RVESV), and RV ejection fraction (RVEF) were obtained using fully automated three-dimensional RV quantification software and compared with a CMR reference. For inter-technical agreement, Spearman correlation and Bland–Altman analysis were used.Results: The fully automated RV quantification software was feasible in 149 patients. RVEDV and RVESV were underestimated, and RVEF was overestimated compared with CMR values. RV measurements obtained from the manual editing method correlated better with CMR values than that without manual editing (RVEDV, 0.924 vs. 0.794: RVESV, 0.955 vs. 0.854; RVEF, 0.941 vs. 0.781 respectively, all p < 0.0001) with less bias and narrower limit of agreement (LOA). The bias and LOA for RV volumes and EF using the automated software without and with manual editing were greater in patients with severely impaired RV function or low frame rate than those with normal and mild impaired RV function, or high frame rate. The fully automated RV three-dimensional measurements were highly reproducible.Conclusion: The novel fully automated RV software shows good feasibility and reproducibility, and the measurements had a high correlation with CMR values. These findings support the routine application of the novel 3D automated RV software in clinical practice.

Speckle tracking during stress echocardiography using high frame rate imaging

Abstract Background As many cardiac diseases do not lead to symptoms under resting conditions, subjecting the patient to a stress (e.g. exercise) test is clinical routine to reveal disease. Quantification of cardiac function using speckle tracking echocardiography (STE) during such stress test remains a challenge not only as overall image quality typically drops but also as the heart rate increases which results in an unfavourable heart-rate-to-frame-rate ratio as required for robust tracking. Moreover, conventional STE runs at relatively low frame rate thereby under-resolving peak strain rate (SR) values – which is particularly true at high heart rates – while this biomarker has been shown to better disclose stress-induced disease than strain using Tissue Doppler Imaging (TDI)-based strain methodologies. Purpose The aim of this study was therefore to test whether HFR STE could reveal the strain / SR response described previously in the TDI literature. Methods Stress echocardiography was performed in 25 healthy volunteers at four different stress levels (baseline, 25%, 50% and 66% of maximum workload) using a supine bike. Apical 4-chamber views were recorded using the ULA-OP 256 experimental scanner running a HFR sequence based on the compounding of 6 diverging wave transmits to achieve a frame rate of 833Hz. A myocardial contour was manually drawn on the reconstructed images and tracked during the cardiac cycle by a custom-made 2D HFR STE algorithm (DOI: 10.1109/TUFFC.2020.2985451). Then, strain and strain rate curves were computed from which systolic (S) and diastolic (early (E) and late (A)) peak values, as well as the short-lived isovolumic relaxation peak (IVR) were extracted. Finally, these values were compared amongst the different stress levels using a single factor ANOVA. Results Some datasets had to be discarded as the contour was not properly tracked at a visual assessment of an expert cardiologist. Tracking was feasible in 92%, 98%, 80% and 64% of cases, for baseline, 25%, 50% and 66% of maximum workload, respectively. The decreasing feasibility with exercise level is in line with what is seen clinically, as volunteers' breathing is faster and heavier with increasing exercise level making the imaging more challenging. The extracted strain and SR curves showed a physiological pattern (Fig. 1a). As shown in Fig. 1b, the global systolic strain response was biphasic, showing a significant increase at low stress level but then reaching a plateau. In contrast, all SR indices linearly increased at each stress level. Conclusion Strain rate clinical markers extracted with HFR STE are concordant with what was reported in TDI literature. These findings show that HFR STE allows to assess cardiac function adequately during stress echocardiography. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): FWO - Research Foundation Flanders

Using polynomial modeling for calculation of sperm quality parameters in CASA

Measurement of sperm velocity parameters takes an important place in sperm analysis. Today, computer-assisted sperm analysis (CASA) systems are used to detect motility measurements such as VCL (Curvilinear Velocity), VSL (Linear Velocity) and VAP (Average Path Velocity). The path length of sperm cells is necessary to calculate the motility parameters and it is calculated using video processing. However, this path length is obtained by the discrete-time processing of video frames, which can lead to unrealistic results. In CASA systems, the frame rate of the videos is increased to obtain the natural path length, but in this case, it is necessary to increase the hardware cost as well. Polynomial modeling applied to measure the natural path length in discrete-time structures can solve this problem. In this study, Lagrange interpolation which is an effective polynomial modeling method was used to obtain the natural path length and velocity parameters of the sperm. The results of the study showed that, when applied the polynomial modeling to calculate VCL and VAP parameters, it was found that especially in the low frame rate, more effective data were obtained than the classical method. As a result of this study, it is recommended to use polynomial modeling in the sperm velocity calculations of CASA systems, although there is an increase in calculation time.

High quality recordings and transcriptions of speech via remote platforms

High quality recordings and transcriptions of speech are important to a wide variety of disciplines from linguistics and human language technology to biomedical screening, diagnosis and tracking. The wide availability of internet connections and powerful mobile devices offers low cost opportunities for collecting speech data at scale. But even in the era of open source software, numerous challenges remain. For example, video call applications such as Zoom have become widespread and allow for recording, but only provide lossy codecs with low frame rates, and often contain missing, repeated, or interpolated frames, as well as freezes, longer dropouts and other audio artefacts. LDC has recently developed a suite of tools to allow high quality internet-based audio recordings and transcription, with a premium on portability and flexibility, using secure cloud computing services for storage and back-end processing. We present here the current design and capabilities of our software, as well as availability in terms of open source code and app distribution. We also discuss future plans; planned capabilities include 2 + sided conversational recordings, connecting participants via the internet, a modern extension of Conversational Telephone Speech (CTS) collections.

Low Thermal Expansion Machine Frame Designs Using Lattice Structures

In this work, we investigated tessellating cellular (or lattice) structures for use in a low thermal expansion machine frame. We proposed a concept for a lattice structure with tailorable effective coefficient of thermal expansion (CTE). The design is an assembly of two parts: a lattice outer part and a cylindrical inner part, which are made of homogenous materials with different positive CTEs. Several lattice design variations were investigated and their thermal and mechanical performance analysed using a finite element method. Our numerical models showed that a lattice design using Nylon 12 and ultra-high molecular weight polyethylene could yield an effective in-plane CTE of 1 × 10−9 K−1 (cf. 109 × 10−6 K−1 for solid Nylon 12). This paper showed that the combination of design optimisation and additive manufacturing can be used to achieve low CTE structures and, therefore, low thermal expansion machine frames of a few tens of centimetres in height.

Research on Low Frame Rate Video Compression Algorithm in the Context of New Media

When using the current method to compress the low frame rate video animation video, there is no frame rate compensation for the video image, which cannot eliminate the artifacts generated in the compression process, resulting in low definition, poor quality, and low compression efficiency of the compressed low frame rate video animation video. In the context of new media, the linear function model is introduced to study the frame rate video animation video compression algorithm. In this paper, an adaptive detachable convolutional network is used to estimate the offset of low frame rate video animation using local convolution. According to the estimation results, the video frames are compensated to eliminate the artifacts of low frame rate video animation. After the frame rate compensation, the low frame rate video animation video is divided into blocks, the CS value of the image block is measured, the linear estimation of the image block is carried out by using the linear function model, and the compression of the low frame rate video animation video is completed according to the best linear estimation result. The experimental results show that the low frame rate video and animation video compressed by the proposed algorithm have high definition, high compression quality under different compression ratios, and high compression efficiency under different compression ratios.

Three-Dimensional Stereo Vision Tracking of Multiple Free-Swimming Fish for Low Frame Rate Video

Three-dimensional multiple fish tracking has gained significant research interest in quantifying fish behavior. However, most tracking techniques use a high frame rate, which is currently not viable for real-time tracking applications. This study discusses multiple fish-tracking techniques using low-frame-rate sampling of stereo video clips. The fish were tagged and tracked based on the absolute error of the predicted indices using past and present fish centroid locations and a deterministic frame index. In the predictor sub-system, linear regression and machine learning algorithms intended for nonlinear systems, such as the adaptive neuro-fuzzy inference system (ANFIS), symbolic regression, and Gaussian process regression (GPR), were investigated. The results showed that, in the context of tagging and tracking accuracy, the symbolic regression attained the best performance, followed by the GPR, that is, 74% to 100% and 81% to 91%, respectively. Considering the computation time, symbolic regression resulted in the highest computing lag of approximately 946 ms per iteration, whereas GPR achieved the lowest computing time of 39 ms.

External GFRP confinement to decrease near-fault earthquake damage of reinforced concrete structures considering soil-structure interaction

In this study, low and medium-rise non-ductile RC frame structures were selected and strengthened by external GFRP confinement. Non-linear time-history analyses, followed by damage analyses, were carried out for the un-strengthened and strengthened frames under different near/far-fault earthquakes, without and with soil-structure interaction (SSI). The obtained results indicated that the external GFRP confinement successfully prevents the collapse of non-ductile RC frames located in near-fault areas in 2 km proximity to the fault. In 5–10 km proximity to the fault, GFRP confinement reduces the damage from severe damage to moderate damage or from moderate damage to light damage. The results also reaffirm that external GFRP confinement can be effective to fix design errors. With raft foundation on stiff soil, the SSI effect on near-fault earthquake damage of the frames can be negligible. These conclusions can be helpful for mitigating the seismic risk of 1970s-code-compliance or design-error structures.

Thermal Imaging Metrology Using High Dynamic Range Near-Infrared Photovoltaic-Mode Camera.

The measurement of a wide temperature range in a scene requires hardware capable of high dynamic range imaging. We describe a novel near-infrared thermal imaging system operating at a wavelength of 940 nm based on a commercial photovoltaic mode high dynamic range camera and analyse its measurement uncertainty. The system is capable of measuring over an unprecedently wide temperature range; however, this comes at the cost of a reduced temperature resolution and increased uncertainty compared to a conventional CMOS camera operating in photodetective mode. Despite this, the photovoltaic mode thermal camera has an acceptable level of uncertainty for most thermal imaging applications with an NETD of 4–12 °C and a combined measurement uncertainty of approximately 1% K if a low pixel clock is used. We discuss the various sources of uncertainty and how they might be minimised to further improve the performance of the thermal camera. The thermal camera is a good choice for imaging low frame rate applications that have a wide inter-scene temperature range.

Multi-exposure interferometric diffusing wave spectroscopy.

We present multi-exposure interferometric diffusing wave spectroscopy (MiDWS), which measures brain blood flow index (BFI) continuously and non-invasively. MiDWS employs interferometry to detect low light levels, probing the optical field autocorrelation indirectly by varying the sensor exposure time. Here MiDWS is compared with conventional interferometric diffusing wave spectroscopy and speckle contrast optical spectroscopy in phantoms. Notably, the MiDWS approach enables the use of low frame rate, two-dimensional complementary metal-oxide semiconductor cameras in a short exposure time regime, where detector noise greatly exceeds the sample photon count. Finally, we show that MiDWS can monitor the BFI simultaneously at two source-collector separations (1 and 3 cm) on the adult human head on a single camera, enabling the use of superficial signal regression techniques to improve brain specificity.