Changes in postural sway and its fractions in conditions of postural instability

We investigated changes in postural sway and its fractions associated with manipulations of the dimensions of the support area. Nine healthy adults stood as quietly as possible, with their eyes open, on a force plate as well as on 5 boards with reduced support area. The center of pressure (COP) trajectory was computed and decomposed into rambling (Rm) and trembling (Tr) trajectories. Sway components were quantified using RMS (root mean square) value, average velocity, and sway area. During standing on the force plate, the RMS was larger for the anterior-posterior (AP) sway components than for the mediolateral (ML) components. During standing on boards with reduced support area, sway increased in both directions. The increase was more pronounced when standing on boards with a smaller support area. Changes in the larger dimension of the support area also affected sway, but not as much as changes in the smaller dimension. ML instability had larger effects on indices of sway compared to AP instability. The average velocity of Rm was larger while the average velocity of Tr was smaller in the AP direction vs. the ML direction. The findings can be interpreted within the hypothesis of an active search function of postural sway. During standing on boards with reduced support area, increased sway may by itself lead to loss of balance. The findings also corroborate the hypothesis of Duarte and Zatsiorsky that Rm and Tr reveal different postural control mechanisms.     

Simultaneous intracellular recording and calcium imaging in single neurons of hippocampal slices

Fluorescent Ca2+ indicator dyes can be introduced into cells through the same microelectrode used for intracellular voltage recording. Simultaneous measurement of cell membrane potential and intracellular Ca2+ concentration can be very helpful in interpreting the mechanisms of Ca2+ increases. This chapter describes fluorescence image acquisition using a CCD camera and a computer program that also records a synchronized membrane potential trace. The same program allows for preliminary data analysis. More elaborate analyses can be accomplished with commercial programs. We also describe quantitative evaluations of sources of error in the use of the statistic deltaF/F as an indicator of Ca2+ concentration. Especially important errors to minimize are changes in background fluorescence and inappropriate autofluorescence corrections. Some improvement of fluorescence images of cells deep within slices may be accomplished by masking. One method is described for making a mask based on the raw fluorescence image. With another method, highly detailed cell morphologies may be conveyed by using masks based on neurobiotin injections and camera lucida drawings.     

Automated location invariant animal detection in camera trap images using publicly available data sources

1. A time‐consuming challenge faced by camera trap practitioners is the extraction of meaningful data from images to inform ecological management. An increasingly popular solution is automated image classification software. However, most solutions are not sufficiently robust to be deployed on a large scale due to lack of location invariance when transferring models between sites. This prevents optimal use of ecological data resulting in significant expenditure of time and resources to annotate and retrain deep learning models.
2. We present a method ecologists can use to develop optimized location invariant camera trap object detectors by (a) evaluating publicly available image datasets characterized by high intradataset variability in training deep learning models for camera trap object detection and (b) using small subsets of camera trap images to optimize models for high accuracy domain‐specific applications.
3. We collected and annotated three datasets of images of striped hyena, rhinoceros, and pigs, from the image‐sharing websites FlickR and iNaturalist (FiN), to train three object detection models. We compared the performance of these models to that of three models trained on the Wildlife Conservation Society and Camera CATalogue datasets, when tested on out‐of‐sample Snapshot Serengeti datasets. We then increased FiN model robustness by infusing small subsets of camera trap images into training.
4. In all experiments, the mean Average Precision (mAP) of the FiN trained models was significantly higher (82.33%–88.59%) than that achieved by the models trained only on camera trap datasets (38.5%–66.74%). Infusion further improved mAP by 1.78%–32.08%.
5. Ecologists can use FiN images for training deep learning object detection solutions for camera trap image processing to develop location invariant, robust, out‐of‐the‐box software. Models can be further optimized by infusion of 5%–10% camera trap images into training data. This would allow AI technologies to be deployed on a large scale in ecological applications. Datasets and code related to this study are open source and available on this repository: https://doi.org/10.5061/dryad.1c59zw3tx.

     

Coded-exposure camera and its circuits design

In the industrial production line, the motion of the target is the main reason for blurred image of the camera monitoring. A coded-exposure devices and circuits are designed to get restored image from this motion blurring. A given binary code sequence which represent open or close of shutter in CCD circuits driven by FPGA is used to control the exposure-time. The sampled images are processed by deconvolution algorithm and the high frequency information of them could be preserved by using the coded-exposure sequence resulting in blurred image restoration. The de-blurred problem could be converted to a well-posed from an ill-posed one. Experiments demonstrate that using the coded-exposure, the device proposed is able to improve the quality of blurred image.     

Time resolved imaging microscopy. Phosphorescence and delayed fluorescence imaging.

An optical microscope capable of measuring time resolved luminescence (phosphorescence and delayed fluorescence) images has been developed. The technique employs two phase-locked mechanical choppers and a slow-scan scientific CCD camera attached to a normal fluorescence microscope. The sample is illuminated by a periodic train of light pulses and the image is recorded within a defined time interval after the end of each excitation period. The time resolution discriminates completely against light scattering, reflection, autofluorescence, and extraneous prompt fluorescence, which ordinarily decrease contrast in normal fluorescence microscopy measurements. Time resolved image microscopy produces a high contrast image and particular structures can be emphasized by displaying a new parameter, the ratio of the phosphorescence to fluorescence. Objects differing in luminescence decay rates are easily resolved. The lifetime of the long lived luminescence can be measured at each pixel of the microscope image by analyzing a series of images that differ by a variable time delay. The distribution of luminescence decay rates is displayed directly as an image. Several examples demonstrate the utility of the instrument and the complementarity it offers to conventional fluorescence microscopy.     

A Flexible Calibration Method Using the Planar Target with a Square Pattern for Line Structured Light Vision System

A flexible calibration approach for line structured light vision system is proposed in this paper. Firstly a camera model is established by transforming the points from the 2D image plane to the world coordinate frame, and the intrinsic parameters of camera can be obtained accurately. Then a novel calibration method for structured light projector is presented by moving a planar target with a square pattern randomly, and the method mainly involves three steps: first, a simple linear model is proposed, by which the plane equation of the target at any orientations can be determined based on the square’s geometry information; second, the pixel coordinates of the light stripe center on the target images are extracted as the control points; finally, the points are projected into the camera coordinate frame with the help of the intrinsic parameters and the plane equations of the target, and the structured light plane can be determined by fitting these three-dimensional points. The experimental data show that the method has good repeatability and accuracy.     

Image analysis of oronasal fistulas in cleft palate patients acquired with an intraoral camera

The aim of this study was to examine the clinical technique of using an intraoral camera to monitor the size of residual oronasal fistulas in cleft lip-cleft palate patients, to assess its repeatability on study casts and patients, and to compare its use with other methods. Seventeen plaster study casts of cleft palate patients with oronasal fistulas obtained from a 5-year series of 160 patients were used. For the clinical study, 13 patients presenting in a clinic prospectively over a 1-year period were imaged twice by the camera. The area of each fistula on each study cast was measured in the laboratory first using a previously described graph paper and caliper technique and second with the intraoral camera. Images were imported into a computer and subjected to image enhancement and area measurement. The camera was calibrated by imaging a standard periodontal probe within the fistula area. The measurements were repeated using a double-blind technique on randomly renumbered casts to assess the repeatability of measurement of the methods. The clinical images were randomly and blindly numbered and subjected to image enhancement and processing in the same way as for the study casts. Area measurements were computed. Statistical analysis of repeatability of measurement using a paired sample t test showed no significant difference between measurements, indicating a lack of systematic error. An intraclass correlation coefficient of 0.97 for the graph paper and 0.84 for the camera method showed acceptable random error between the repeated records for each of the two methods. The graph paper method remained slightly more repeatable. The mean fistula area of the study casts between each method was not statistically different when compared with a paired samples t test (p = 0.08). The methods were compared using the limits of agreement technique, which showed clinically acceptable repeatability. The clinical study of repeated measures showed no systematic differences when subjected to a t test (p = 0.109) and little random error with an intraclass correlation coefficient of 0.98. The fistula size seen in the clinical study ranged from 18.54 to 271.55 mm. Direct measurements subsequently taken on 13 patients in the clinic without study models showed a wide variation in the size of residual fistulas presenting in a multidisciplinary clinic. It was concluded that an intraoral camera method could be used in place of the previous graph paper method and could be developed for clinical and scientific purposes. This technique may offer advantages over the graph paper method, as it facilitates easy visualization of oronasal fistulas and objective fistulas size determination and permits easy storage of data in clinical records.     

A rapid method for the estimation of rock surface areas

A method is described for estimating the surface area of irregular-shaped objects, specifically river rocks in the weight range 150–450 g, using a surface coating material and image analysis. The objects are dipped in molten Gelflex®, a PVC resin, which when hardened is peeled off in sections and scanned using a lightbox, camera and appropriate image analysis software. The method is quick, inexpensive, non-destructive, precise and reasonably accurate (within 3.4%) where large numbers of objects are involved.     

Concurrent Visualization of Acoustic Radiation Force Displacement and Shear Wave Propagation with 7T MRI

Manual palpation is a common and very informative diagnostic tool based on estimation of changes in the stiffness of tissues that result from pathology. In the case of a small lesion or a lesion that is located deep within the body, it is difficult for changes in mechanical properties of tissue to be detected or evaluated via palpation. Furthermore, palpation is non-quantitative and cannot be used to localize the lesion. Magnetic Resonance-guided Focused Ultrasound (MRgFUS) can also be used to evaluate the properties of biological tissues non-invasively. In this study, an MRgFUS system combines high field (7T) MR and 3 MHz focused ultrasound to provide high resolution MR imaging and a small ultrasonic interrogation region (~0.5 x 0.5 x 2 mm), as compared with current clinical systems. MR-Acoustic Radiation Force Imaging (MR-ARFI) provides a reliable and efficient method for beam localization by detecting micron-scale displacements induced by ultrasound mechanical forces. The first aim of this study is to develop a sequence that can concurrently quantify acoustic radiation force displacements and image the resulting transient shear wave. Our motivation in combining these two measurements is to develop a technique that can rapidly provide both ARFI and shear wave velocity estimation data, making it suitable for use in interventional radiology. Secondly, we validate this sequence in vivo by estimating the displacement before and after high intensity focused ultrasound (HIFU) ablation, and we validate the shear wave velocity in vitro using tissue-mimicking gelatin and tofu phantoms. Such rapid acquisitions are especially useful in interventional radiology applications where minimizing scan time is highly desirable.     

基于径向基函数神经网络的肺部加权频差电阻抗成像方法

目的 对肺通气过程进行床旁实时连续图像监控，是机械通气患者和临床医生的迫切需求。肺部电阻抗成像（EIT）可反映呼吸引起的胸腔电特性变化分布，在肺通气监测方面具有天然的优势。本文目的在于建立基于径向基函数神经网络（RBFNN）的肺部加权频差电阻抗成像（wfd-EIT）方法，实现对肺通气的高空间分辨率成像。方法 利用肺部wfd-EIT成像方法实时描绘胸腔电导率分布状况，再通过RBFNN将目标区域可视化并精准识别其边界信息。首先通过数值分析模拟，在各个激励频率利用COMSOL与MATLAB软件建立2 028个仿真样本，分为训练样本集和测试样本集，验证所提出成像方法的可行性和有效性。其次，为了验证仿真结果，建立肺部物理模型，选用具有低电导特性的生物组织模拟肺部通气区域，对其进行成像实验，并采用图像相关系数（ICC）和肺区域比（LRR）定量数据衡量成像方法的准确性。结果 wfd-EIT方法可以在任意时刻进行图像重建，并能够准确反映出目标区域的电特性分布；利用基于RBFNN的算法能够增强目标区域的成像精度，ICC可达0.94以上，更好地凸显其边界轮廓信息。结论 通过wfd-EIT成像方法，利用多频阻抗谱同步测量实现目标区域的快速可视化，并结合RBFNN网络逼近任意非线性函数的优点，实现对目标区域电特性变化的精准识别，为下一步进行临床肺通气的EIT图像监测奠定了理论和技术基础。     

基于动态方向梯度矢量流模型的脑肿瘤图像分割

目的:针对GVF Snake模型算法收敛容易陷入局部极小值及对初始轮廓位置敏感等缺点,提出一种动态方向梯度矢量流模型(DDGVF),使其更适合医学图像的分割。方法:利用主动轮廓模型的提取和跟踪特定区域内目标轮廓的方法,将其应用于医学图像如CT、MRI和超声图像的处理,以获取特定器官及组织的轮廓。结果:动态方向梯度矢量流场(DDGVF)能够较好地提取出脑肿瘤图像。结论:利用该方法能够较好地分割提取出脑肿瘤图像的肿瘤病变区域,为进一步对其纹理和形状等特征进行描述和分析提供了可靠的依据。     

Polarization of fluorescently labeled myosin subfragment-1 fully or partially decorating muscle fibers and myofibrils.

Fluorescently labeled myosin heads (S1) were added to muscle fibers and myofibrils at various concentrations. The orientation of the absorption dipole of the dye with respect to the axis of F-actin was calculated from polarization of fluorescence which was measured by a novel method from video images of muscle. In this method light emitted from muscle was split by a birefringent crystal into two nonoverlapping images: the first image was created with light polarized in the direction parallel to muscle axis, and the second image was created with light polarized in the direction perpendicular to muscle axis. Images were recorded by high-sensitivity video camera and polarization was calculated from the relative intensity of both images. The method allows measurement of the fluorescence polarization from single myofibril irrigated with low concentrations of S1 labeled with dye. Orientation was also measured by fluorescence-detected linear dichroism. The orientation was different when muscle was irrigated with high concentration of S1 (molar ratio S1:actin in the I bands equal to 1) then when it was irrigated with low concentration of S1 (molar ratio S1:actin in the I bands equal to 0.32). The results support our earlier proposal that S1 could form two different rigor complexes with F-actin depending on the molar ratio of S1:actin.     

Field measurements of wind speed and reconfiguration in Arundo donax (Poaceae) with estimates of drag forces

The giant reed (Arundo donax) is well known as a species that can withstand high wind loads without mechanical damage. To examine wind impact, profiles of vertical wind speeds in the plant's natural habitat (southern France) were measured at the edge and within a stand in the main wind direction. Wind speed was recorded simultaneously at five heights. For 75 measurements of within-canopy wind speed profiles, the attenuation coefficient was 4.4 ± 0.5, a value typical for plant stands with very dense canopies. Video recordings proved that A. donax becomes streamlined with increasing wind speed, reducing the projected surface area of leaves and stem. The total projected surface area is a function of wind speed and can be characterized by a second-order polynomial regression curve. For small wind velocities up to 1 m/s, the calculated drag force is proportional to the square of the wind speed. However, when A. donax plants are subjected to higher wind speeds (1.5-10 m/s), the drag force becomes directly proportional to the wind speed. Streamlining is a potentially important adaptation for withstanding high wind loads, especially for individual plants and plants at the edge of stands, whereas in dense stands streamlining probably plays a minor role.     

Quantifying fungal infection of plant leaves by digital image analysis using Scion Image software

A digital image analysis method previously used to evaluate leaf color changes due to nutritional changes was modified to measure the severity of several foliar fungal diseases. Images captured with a flatbed scanner or digital camera were analyzed with a freely available software package, Scion Image, to measure changes in leaf color caused by fungal sporulation or tissue damage. High correlations were observed between the percent diseased leaf area estimated by Scion Image analysis and the percent diseased leaf area from leaf drawings. These drawings of various foliar diseases came from a disease key previously developed to aid in visual estimation of disease severity. For leaves of Nicotiana benthamiana inoculated with different spore concentrations of the anthracnose fungus Colletotrichum destructivum, a high correlation was found between the percent diseased tissue measured by Scion Image analysis and the number of leaf spots. The method was adapted to quantify percent diseased leaf area ranging from 0 to 90% for anthracnose of lily-of-the-valley, apple scab, powdery mildew of phlox and rust of golden rod. In some cases, the brightness and contrast of the images were adjusted and other modifications were made, but these were standardized for each disease. Detached leaves were used with the flatbed scanner, but a method using attached leaves with a digital camera was also developed to make serial measurements of individual leaves to quantify symptom progression. This was successfully applied to monitor anthracnose on N. benthamiana leaves. Digital image analysis using Scion Image software is a useful tool for quantifying a wide variety of fungal interactions with plant leaves.     

DEVELOPMENT OF ARTIFICIAL NEURAL NETWORKS CAPABLE OF IDENTIFYING CRYPTOSPORIDIUM PARVUM OOCYSTS STAINED WITH 4', 6 DIAMIDINO-2-PHENYLINDOLE

Cryptosporidium parvum is a coccidian protozoan parasite capable of infecting a variety of mammalian hosts, and can cause gastro-enteric disease within humans. C. parvum oocysts were stained with varying concentrations of 4', 6 diamidino-2-phenylindole (DAPI). After microscopic observation, objects of interest were captured using a CCD color digital camera. The microscopic images were classified based on their DAPI stain properties as either DAPI positive or negative. Individual oocysts were cropped, converted to grayscale, applied to a binary threshold filter, and were further processed into a numerical data array. DAPI positive and negative images (100 each) were randomly removed for artificial neural network (ANN) testing. The remaining image data were used for ANN training using a commercially available software program. After training experimentation, a final network design was implemented possessing 95 input, 400 hidden, and 2 output neurons. Additional control image sets (ranging from 165 to 119 images) were collected to better ascertain ANN performance. These images consisted of DAPI positive oocysts and two types of DAPI negative images (either formalin treated oocysts or algal cultures). Selected ANN correctly identified, as a range, 82.4–93.8% of the DAPI positive oocysts, 97–98.2% of the DAPI negative oocysts, and 52.9–57% of the DAPI negative algal cells. The control image sets were unique data, never presented during ANN training. Because of this, combined with the high number of correct image identifications for certain image sets, ANN technology may provide a means to identify C. parvum oocysts through automated analysis.     

Quick and efficient measurement of transient GUS expression using image analysis

An image-analysis procedure was developed for measurement of transient β-glucuronidase (GUS) gene expression events in peanut. Gene transfer via microprojectile bombardment has been effective in peanut. Experiments were performed to improve the efficiency of DNA delivery to embryogenic calli for transformation. Transient GUS expression was assayed 24 hours after bombardment by staining calli and manually counting blue-stained spots under a microscope. These calli were then placed under a dissecting microscope with a video camera that recorded each image onto a computer. The images were then subjected to analysis with software that counted the number of blue-stained GUS-positive spots as well as the area and percent of the total area of each spot. The manual counts and data from the image analysis were compared through correlation statistics and by comparing analyses of variance for fixed parameters of the experiments. Correlation coefficients were high between manual spot counts and image-analysis counts (r=0.77) and between manual counts and percent area (GUS (r=0.91) Results indicate that image analysis provides a quick and efficient method for analysis of transient expression. Much more reliable information is obtained with less effort and less fatigue with the image-analysis procedure. Scientists can use this method to monitor transient expression events in plant transformation experiments.     

Digital Inline Holographic Microscopy (DIHM) of Weakly-scattering Subjects

Weakly-scattering objects, such as small colloidal particles and most biological cells, are frequently encountered in microscopy. Indeed, a range of techniques have been developed to better visualize these phase objects; phase contrast and DIC are among the most popular methods for enhancing contrast. However, recording position and shape in the out-of-imaging-plane direction remains challenging. This report introduces a simple experimental method to accurately determine the location and geometry of objects in three dimensions, using digital inline holographic microscopy (DIHM). Broadly speaking, the accessible sample volume is defined by the camera sensor size in the lateral direction, and the illumination coherence in the axial direction. Typical sample volumes range from 200 µm x 200 µm x 200 µm using LED illumination, to 5 mm x 5 mm x 5 mm or larger using laser illumination. This illumination light is configured so that plane waves are incident on the sample. Objects in the sample volume then scatter light, which interferes with the unscattered light to form interference patterns perpendicular to the illumination direction. This image (the hologram) contains the depth information required for three-dimensional reconstruction, and can be captured on a standard imaging device such as a CMOS or CCD camera. The Rayleigh-Sommerfeld back propagation method is employed to numerically refocus microscope images, and a simple imaging heuristic based on the Gouy phase anomaly is used to identify scattering objects within the reconstructed volume. This simple but robust method results in an unambiguous, model-free measurement of the location and shape of objects in microscopic samples.     

Influence of leg stiffness and its effect on myodynamic jumping performance.

The purposes of this study are: a) to examine the possibility of influencing the leg stiffness through instructions given to the subjects and b) to determine the effect of the leg stiffness on the mechanical power and take-off velocity during the drop jumps. A total of 15 athletes performed a series of drop jumps from heights of 20, 40 and 60 cm. The instructions given to the subjects were a) "jump as high as you can" and b) "jump high a little faster than your previous jump". The jumps were performed at each height until the athlete could not achieve a shorter ground contact time. The ground reaction forces were measured using a "Kistler" force plate (1000 Hz). The athletes body positions were recorded using a high speed (250 Hz) video camera. EMG was used to measure muscle activity in five leg muscles. The data was divided into 5 groups where group 1 was made up of the longest ground contact times of each athlete and group 5 the shortest. The leg and ankle stiffness values were higher when the contact times were shorter. This means that by influencing contact time through verbal instructions it is possible to control leg stiffness. Maximum center of mass take-off velocity the can be achieved with different levels of leg stiffness. The mechanical power acting on the human body during the positive phase of the drop jumps had the highest values in group 3. This means that there is an optimum stiffness value for the lower extremities to maximize mechanical power.     

A method for measurement of joint kinematics in vivo by registration of 3-D geometric models with cine phase contrast magnetic resonance imaging data

A new method is presented for measuring joint kinematics by optimally matching modeled trajectories of geometric surface models of bones with cine phase contrast (cine-PC) magnetic resonance imaging data. The incorporation of the geometric bone models (GBMs) allows computation of kinematics based on coordinate systems placed relative to full 3-D anatomy, as well as quantification of changes in articular contact locations and relative velocities during dynamic motion. These capabilities are additional to those of cine-PC based techniques that have been used previously to measure joint kinematics during activity. Cine-PC magnitude and velocity data are collected on a fixed image plane prescribed through a repetitively moved skeletal joint. The intersection of each GBM with a simulated image plane is calculated as the model moves along a computed trajectory, and cine-PC velocity data are sampled from the regions of the velocity images within the area of this intersection. From the sampled velocity data, the instantaneous linear and angular velocities of a coordinate system fixed to the GBM are estimated, and integration of the linear and angular velocities is used to predict updated trajectories. A moving validation phantom that produces motions and velocity data similar to those observed in an experiment on human knee kinematics was designed. This phantom was used to assess cine-PC rigid body tracking performance by comparing the kinematics of the phantom measured by this method to similar measurements made using a magnetic tracking system. Average differences between the two methods were measured as 2.82 mm rms for anterior/posterior tibial position, and 2.63 deg rms for axial rotation. An intertrial repeatability study of human knee kinematics using the new method produced rms differences in anterior/posterior tibial position and axial rotation of 1.44 mm and 2.35 deg. The performance of the method is concluded to be sufficient for the effective study of kinematic changes caused to knees by soft tissue injuries.     

Developing a multi-Kinect-system for monitoring in dairy cows: object recognition and surface analysis using wavelets

Camera-based systems in dairy cattle were intensively studied over the last years. Different from this study, single camera systems with a limited range of applications were presented, mostly using 2D cameras. This study presents current steps in the development of a camera system comprising multiple 3D cameras (six Microsoft Kinect cameras) for monitoring purposes in dairy cows. An early prototype was constructed, and alpha versions of software for recording, synchronizing, sorting and segmenting images and transforming the 3D data in a joint coordinate system have already been implemented. This study introduced the application of two-dimensional wavelet transforms as method for object recognition and surface analyses. The method was explained in detail, and four differently shaped wavelets were tested with respect to their reconstruction error concerning Kinect recorded depth maps from different camera positions. The images’ high frequency parts reconstructed from wavelet decompositions using the haar and the biorthogonal 1.5 wavelet were statistically analyzed with regard to the effects of image fore- or background and of cows’ or persons’ surface. Furthermore, binary classifiers based on the local high frequencies have been implemented to decide whether a pixel belongs to the image foreground and if it was located on a cow or a person. Classifiers distinguishing between image regions showed high (⩾0.8) values of Area Under reciever operation characteristic Curve (AUC). The classifications due to species showed maximal AUC values of 0.69.