[Interpolation Algorithm for Motion Vector Field of CTA Image and Accelerated Implementation Based on Uniform Grid and Multi-level B-spline].

In order to solve the problems of slow operation speed and low registration accuracy of thin plate spline (TPS) interpolation method for motion vector field in coronary computed tomography angiography (CTA), a multi-level B-spline interpolation method (MBS) with uniform grid is proposed. On the one hand, the interpolation method used local B-spline to refine the sparse mesh layer by layer in a multiscale way to improve the accuracy of registration. On the other hand, it used the splitting matrix method to interpolate the motion vector field, greatly reducing the operation time of interpolation. The experimental results show that the proposed method can be used for CTA image registration efficiently.

Analysis of electro-mechanical relationship in human iPS cell-derived cardiomyocytes sheets under proarrhythmic condition assessed by simultaneous field potential and motion vector recordings.

We investigated the electro-mechanical relationship of human iPS cell-derived cardiomyocyte sheets under arrhythmic condition, which was induced by digitalis intoxication along with the electrical train stimulation (n = 4). We adopted motion vector analysis by high-speed video microscopy and extracellular field potential recording by 64-microelectrode array system. The motion vector analysis uncovered local contractile events at resting phase, at which the field potential analysis showed no deflection in any cell sheet. Thus, motion vector analysis may provide supplemental information over field potential recording in detecting Ca2+-triggered arrhythmias, which may become a new strategy for assessing arrhythmic liability of test articles.

Front-Vehicle Detection in Video Images Based on Temporal and Spatial Characteristics.

Assisted driving and unmanned driving have been areas of focus for both industry and academia. Front-vehicle detection technology, a key component of both types of driving, has also attracted great interest from researchers. In this paper, to achieve front-vehicle detection in unmanned or assisted driving, a vision-based, efficient, and fast front-vehicle detection method based on the spatial and temporal characteristics of the front vehicle is proposed. First, a method to extract the motion vector of the front vehicle is put forward based on Oriented FAST and Rotated BRIEF (ORB) and the spatial position constraint. Then, by analyzing the differences between the motion vectors of the vehicle and those of the background, feature points of the vehicle are extracted. Finally, a feature-point clustering method based on a combination of temporal and spatial characteristics are applied to realize front-vehicle detection. The effectiveness of the proposed algorithm is verified using a large number of videos.

Real-Time Eyeblink Detector and Eye State Classifier for Virtual Reality (VR) Headsets (Head-Mounted Displays, HMDs).

The aim of the study is to develop a real-time eyeblink detection algorithm that can detect eyeblinks during the closing phase for a virtual reality headset (VR headset) and accordingly classify the eye's current state (open or closed). The proposed method utilises analysis of a motion vector for detecting eyelid closure, and a Haar cascade classifier (HCC) for localising the eye in the captured frame. When the downward motion vector (DMV) is detected, a cross-correlation between the current region of interest (eye in the current frame) and a template image for an open eye is used for verifying eyelid closure. A finite state machine is used for decision making regarding eyeblink occurrence and tracking the eye state in a real-time video stream. The main contributions of this study are, first, the ability of the proposed algorithm to detect eyeblinks during the closing or the pause phases before the occurrence of the reopening phase of the eyeblink. Second, realising the proposed approach by implementing a valid real-time eyeblink detection sensor for a VR headset based on a real case scenario. The sensor is used in the ongoing study that we are conducting. The performance of the proposed method was 83.9% for accuracy, 91.8% for precision and 90.40% for the recall. The processing time for each frame took approximately 11 milliseconds. Additionally, we present a new dataset for non-frontal eye monitoring configuration for eyeblink tracking inside a VR headset. The data annotations are also included, such that the dataset can be used for method validation and performance evaluation in future studies.

Entropy-Based Video Steganalysis of Motion Vectors.

In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes.

A Hierarchical Framework Combining Motion and Feature Information for Infrared-Visible Video Registration.

In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotation prior to matching. In precise registration based on keypoint matching, the scale and rotation are used in re-location to eliminate their impact on targets and keypoints. To strictly match the keypoints, first, we improve the quality of keypoint matching by using normalized location descriptors and descriptors generated by the histogram of edge orientation. Second, we remove most mismatches by counting the matching directions of correspondences. We tested our framework on a public dataset, where our proposed framework outperformed two recently-proposed state-of-the-art global registration methods in almost all tested videos.

Monocular Vision System for Fixed Altitude Flight of Unmanned Aerial Vehicles.

The fastest and most economical method of acquiring terrain images is aerial photography. The use of unmanned aerial vehicles (UAVs) has been investigated for this task. However, UAVs present a range of challenges such as flight altitude maintenance. This paper reports a method that combines skyline detection with a stereo vision algorithm to enable the flight altitude of UAVs to be maintained. A monocular camera is mounted on the downside of the aircraft's nose to collect continuous ground images, and the relative altitude is obtained via a stereo vision algorithm from the velocity of the UAV. Image detection is used to obtain terrain images, and to measure the relative altitude from the ground to the UAV. The UAV flight system can be set to fly at a fixed and relatively low altitude to obtain the same resolution of ground images. A forward-looking camera is mounted on the upside of the aircraft's nose. In combination with the skyline detection algorithm, this helps the aircraft to maintain a stable flight pattern. Experimental results show that the proposed system enables UAVs to obtain terrain images at constant resolution, and to detect the relative altitude along the flight path.

Image-based evaluation of contraction-relaxation kinetics of human-induced pluripotent stem cell-derived cardiomyocytes: Correlation and complementarity with extracellular electrophysiology.

In this study, we used high-speed video microscopy with motion vector analysis to investigate the contractile characteristics of hiPS-CM monolayer, in addition to further characterizing the motion with extracellular field potential (FP), traction force and the Ca(2+) transient. Results of our traction force microscopy demonstrated that the force development of hiPS-CMs correlated well with the cellular deformation detected by the video microscopy with motion vector analysis. In the presence of verapamil and isoproterenol, contractile motion of hiPS-CMs showed alteration in accordance with the changes in fluorescence peak of the Ca(2+) transient, i.e., upstroke, decay, amplitude and full-width at half-maximum. Simultaneously recorded hiPS-CM motion and FP showed that there was a linear correlation between changes in the motion and field potential duration in response to verapamil (30-150nM), isoproterenol (0.1-10µM) and E-4031 (10-50nM). In addition, tetrodotoxin (3-30µM)-induced delay of sodium current was corresponded with the delay of the contraction onset of hiPS-CMs. These results indicate that the electrophysiological and functional behaviors of hiPS-CMs are quantitatively reflected in the contractile motion detected by this image-based technique. In the presence of 100nM E-4031, the occurrence of early after-depolarization-like negative deflection in FP was also detected in the hiPS-CM motion as a characteristic two-step relaxation pattern. These findings offer insights into the interpretation of the motion kinetics of the hiPS-CMs, and are relevant for understanding electrical and mechanical relationship in hiPS-CMs.

Motion Vector Extrapolation for Video Object Detection.

Despite the continued successes of computationally efficient deep neural network architectures for video object detection, performance continually arrives at the great trilemma of speed versus accuracy versus computational resources (pick two). Current attempts to exploit temporal information in video data to overcome this trilemma are bottlenecked by the state of the art in object detection models. This work presents motion vector extrapolation (MOVEX), a technique which performs video object detection through the use of off-the-shelf object detectors alongside existing optical flow-based motion estimation techniques in parallel. This work demonstrates that this approach significantly reduces the baseline latency of any given object detector without sacrificing accuracy performance. Further latency reductions up to 24 times lower than the original latency can be achieved with minimal accuracy loss. MOVEX enables low-latency video object detection on common CPU-based systems, thus allowing for high-performance video object detection beyond the domain of GPU computing.

A novel analysis of the formation and resorption changes in dental hard tissue using longitudinal in vivo micro computed tomography.

This study was to investigate the new analysis manner of dental hard tissue change using in vivo micro-computed tomography (CT) in rat. Scanning, registration, analyzing, and presenting method to track longitudinal in vivo micro-CT data on dental hard tissues were validated in murine models: formative, dentin thickness after direct pulp capping with mineral trioxide aggregate; resorptive, development of apical bone rarefaction in apical periodontitis model. Serial in vivo micro-CT scans were analyzed through rigid-registration, active-contouring, deformable-registration, and motion vector-based quantitative analyses. The rate and direction of hard tissue formation after direct pulp capping was datafied by tracing coordinate shift of fiducial points on pulp chamber outline in formative model. The development of apical periodontitis could be monitored with voxel counts, and quantitatively analyzed in terms of lesion size, bone loss, and mineral density in resorptive model. This study supports the application of longitudinal in vivo micro-CT for resorptive- and formative-phase specific monitoring of dental hard tissues.

Contractility assessment of human iPSC-derived cardiomyocytes by using a motion vector system and measuring cell impedance.

Predicting drug-induced cardiotoxicity during the non-clinical stage is important to avoid severe consequences in the clinical trials of new drugs. Human iPSC-derived cardiomyocytes (hiPSC-CMs) hold great promise for cardiac safety assessments in drug development. To date, multi-electrode array system (MEA) has been a widely used as a tool for the assessment of proarrhythmic risk with hiPSC-CMs. Recently, new methodologies have been proposed to assess in vitro contractility, such as the force and velocity of cell contraction, using hiPSC-CMs. Herein, we focused on an imaging-based motion vector system (MV) and an electric cell-substrate impedance sensing system (IMP). We compared the output signals of hiPSC-CMs from MV and IMP in detail and observed a clear correlation between the parameters. In addition, we assessed the effects of isoproterenol and verapamil on hiPSC-CM contraction and identified a correlation in the contractile change of parameters obtained with MV and IMP. These results suggest that both assay systems could be used to monitor hiPSC-CM contraction dynamics.

Self-Powered Non-Contact Motion Vector Sensor for Multifunctional Human-Machine Interface.

Sensors as the significant units of the Internet of Things play an important role in the field of information interaction. Non-contact sensors have the advantages of flexible manipulation and a longer lifespan but it is constrained in motion detection due to their relative single detection function. Herein, a self-powered non-contact motion vector sensor (NMVS) for the multifunctional human-machine interface is reported. Based on the electrostatic induction effect, the motion vector is measured according to the output electrical signals from the non-contact triboelectric nanogenerator (NC-TENG). By simulation analysis and experimental validation, the output characteristics of NC-TENG dependence on structural and motion parameters are investigated in detail. On this basis, the resolution of NMVS is improved and exhibits for non-contact micro-vibration monitoring, rehabilitation gait detection, contactless smart lock, and the non-contact limit alarm. This work not only proposes an ingenious strategy for non-contact motion vector detection but also demonstrates the promising prospects of a multifunctional human-machine interface in intelligent electronics, health rehabilitation, and industrial inspection.

Assessment of Contractility in Human iPS Cell-Derived Cardiomyocytes Using Motion Vector Analysis.

Human-induced pluripotent stem cell (iPSC) technology paves the way for next-generation drug-safety assessment. In particular, human iPSC-derived cardiomyocytes, which exhibit electrical activity, are useful as a human cell model for assessing QT-interval prolongation and the risk of the lethal arrhythmia Torsade de Pointes (TdP). In addition to proarrhythmia assay, contractile behavior has received increased attention in drug development. In this study, we developed a novel high-throughput in vitro assay system using motion vectors to evaluate the contractile activity of iPSC-derived cardiomyocytes as a physiologically relevant human platform. The methods presented here highlight the use of commercially available iPSC-derived cardiomyocytes, iCell cardiomyocytes, for contractility evaluation recorded by the motion vector system.

Optimizing the Direction and Order of the Motion Unveiled the Ability of Conventional Monolayers of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes to Show Frequency-Dependent Enhancement of Contraction and Relaxation Motion.

Contractility of the human heart increases as its beating rate is elevated, so-called positive force-frequency relationship; however, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have been reported to exert a negative force-frequency relationship. We tested the hypothesis that the regulation of motion directions by electrical pacing and/or oxygen supply may improve the electro-mechanical properties of hiPSC-CMs monolayers. To better evaluate the spatial and temporal relationship between electrical excitation and contractile motion, we simultaneously observed the field potential and motion vector of hiPSC-CMs sheets. Under spontaneous contraction, although an electrical excitation originating from a region propagated unidirectionally over the cell sheet, contraction wave started from multiple sites, and relaxation wave was initiated from a geometric center of hiPSC-CMs sheet. During electrical pacing, contraction and relaxation waves were propagated from the stimulated site. Interestingly, the maximum contraction speed was more increased when the hiPSC-CMs sheet was stimulated at an area relaxation initiated under spontaneous condition. Furthermore, motion vector analysis demonstrated that "positive contraction velocity-frequency relationship" in contraction and "frequency-dependent enhancement of relaxation" were produced in the cell sheet by optimizing the direction and order of the contractile motion with pacing at the relaxation-initiating area. A close analysis of motion vectors along with field potential recording demonstrated that relaxation process consists of fast and slow phases, and suggest that intracellular Ca2+ dynamics may be closely related to functions of Ca2+-ATPase pump and Na+-Ca2+ exchangers. Namely, the slow relaxation phase occurred after the second peak of field potential, suggesting that the slow phase may be associated with extrusion of Ca2+ by Na+-Ca2+ exchangers during repolarization. Increase of oxygen concentration from 20 to 95% as well as ß-adrenergic stimulation with isoproterenol accelerated the fast relaxation, suggesting that it could depend on Ca2+ uptake via Ca2+-ATPase during the depolarization phase. The ratio of maximum contraction speed to field potential duration was increased by the ß-adrenergic stimulation, indicating the elevated contraction efficiency per Ca2+-influx. Thus, these findings revealed potential ability of conventional monolayers of hiPSC-CMs, which will help apply them to translational study filling the gap between physiological as well as pharmacological studies and clinical practice.

Differential tumor biological role of the tumor suppressor KAI1 and its splice variant in human breast cancer cells.

The tetraspanin and tumor suppressor KAI1 is downregulated or lost in many cancers which correlates with poor prognosis. KAI1 acts via physical/functional crosstalk with other membrane receptors. Also, a splice variant of KAI1 (KAI1-SP) has been identified indicative of poor prognosis. We here characterized differential effects of the two KAI1 variants on tumor biological events involving integrin (αvß3) and/or epidermal growth factor receptor (EGF-R). In MDA-MB-231 and -435 breast cancer cells, differential effects were documented on the expression levels of the tumor biologically relevant integrin αvß3 which colocalized with KAI1-WT but not with KAI1-SP. Cellular motility was assessed by video image processing, including motion detection and vector analysis for the quantification and visualization of cell motion parameters. In MDA-MB-231 cells, KAI1-SP provoked a quicker wound gap closure and higher closure rates than KAI1-WT, also reflected by different velocities and average motion amplitudes of singular cells. KAI1-SP induced highest cell motion adjacent to the wound gap borders, whereas in MDA-MB-435 cells a comparable induction of both KAI1 variants was noticed. Moreover, while KAI1-WT reduced cell growth, KAI1-SP significantly increased it going along with a pronounced EGF-R upregulation. KAI1-SP-induced cell migration and proliferation was accompanied by the activation of the focal adhesion and Src kinase. Our findings suggest that splicing of KAI1 does not only abrogate its tumor suppressive functions, but even more, promotes tumor biological effects in favor of cancer progression and metastasis.

Super-resolution T2-weighted 4D MRI for image guided radiotherapy.

BACKGROUND AND PURPOSE: The superior soft-tissue contrast of 4D-T2w MRI motivates its use for delineation in radiotherapy treatment planning. We address current limitations of slice-selective implementations, including thick slices and artefacts originating from data incompleteness and variable breathing. MATERIALS AND METHODS: A method was developed to calculate midposition and 4D-T2w images of the whole thorax from continuously acquired axial and sagittal 2D-T2w MRI (1.5 × 1.5 × 5.0 mm3). The method employed image-derived respiratory surrogates, deformable image registration and super-resolution reconstruction. Volunteer imaging and a respiratory motion phantom were used for validation. The minimum number of dynamic acquisitions needed to calculate a representative midposition image was investigated by retrospectively subsampling the data (10-30 dynamic acquisitions). RESULTS: Super-resolution 4D-T2w MRI (1.0 × 1.0 × 1.0 mm3, 8 respiratory phases) did not suffer from data incompleteness and exhibited reduced stitching artefacts compared to sorted multi-slice MRI. Experiments using a respiratory motion phantom and colour-intensity projection images demonstrated a minor underestimation of the motion range. Midposition diaphragm differences in retrospectively subsampled acquisitions were <1.1 mm compared to the full dataset. 10 dynamic acquisitions were found sufficient to generate midposition MRI. CONCLUSIONS: A motion-modelling and super-resolution method was developed to calculate high quality 4D/midposition T2w MRI from orthogonal 2D-T2w MRI.