Lower Field Of View Research Articles

Multispectral Imaging for Vein Localization and Contrast Enhancement.

Intravenous (IV) catheterization is a common procedure. Still, there is a 26% chance of the first attempt catheterization failure due to the changing visibility of veins because of the patient's skin tone and body fat content. Ultrasound assistive devices help locate deeper veins but are not practical in emergencies, and transillumination assistive devices have a low field of view. Commercial near-infrared (NIR) imaging devices are effective in vein localization but are expensive and are not used in low-cost clinical settings. To overcome this, NIR Multispectral Imaging (MSI) was used to find the optimal wavelength that provides the enhanced visualization of veins for all skin types and Body Mass Index (BMI). The band with the highest vein-to-skin contrast ratio was selected and contrast enhancement was done using our proposed method. The primary blocks of the proposed method are Gamma correction, Contrast Limited Adaptive Histogram Equalization (CLAHE), Adaptive Thresholding, and image Fusion. The optimal spectral range was found to be 814-876 nm and our method increased the contrast by 0.41, 0.375, and 0.39 for fair, brown, and dark brown skin types, respectively, with different BMI.Clinical relevance- From the study, we can develop a potentially low-cost vein localization assistive device for training medical and nursing students and use it in emergencies for venous access to improve confidence in IV catheterization.

Multistep Super Resolution Double-U-net (SRDUN) for enhancing the resolution of Berea sandstone images

Digital Rock Physics (DRP) has opened a new avenue through the microscale world of rocks leading to more detailed inferences. However, High Resolution (HR) images are problematic from several aspects such as low field of view, huge memory and long time and high cost of image acquisition. Recent advances in Machine Learning (ML) and especially Convolutional Neural Networks (CNN) highly improved the ability of producing HR images from their Low Resolution (LR) counterparts known as Super Resolution (SR) images. In this procedure, the scale-difference between LR and HR images is a key parameter, while a high scale-difference leads to unreliable results regardless of the method. To overcome such a problem, we aim to both propose a multiscale procedure and introduce an efficient network namely Super Resolution Double-U-net (SRDUN). To this end, unlike conventional studies where LR images are synthetically produced from HR images, we capture these images from a Berea sandstone individually in five different scales (16.263, 12.922, 9.499, 5.775 and 3.501 μm for samples with a side of 10, 8, 6, 4 and 2-mm). Then, the SRDUN is introduced, where a first U-net is used to store feature maps of HR images and are imported in a second U-net as informative skip connections. Results show SRDUN could perform more accurate than common networks for small scale-differences. However, when it comes to high scale-differences it becomes more complicated. We propose a multistep procedure, where several mid-step SRDUNs are used to fill the gap of information. Results of this procedure reveal that the multistep procedure could perform much better than the direct approach. These results are then demonstrated by some computations of reservoir parameters such as porosity, pore equivalent diameter distribution, morphometric properties and permeability. Porosity and permeability computations showed that the error of computed values from SR images is increased by increasing scale-difference, however, the multistep procedure leads to more reliable results. The multistep procedure could preserve better the pore size distribution, however, in morphometric properties, the direct approach performs better since the multistep procedure suffers from a smoothing effect.

A Supervised Learning Framework for Joint Estimation of Angles-of-Arrival and Number of Sources

Machine learning is a promising technique for angle-of-arrival (AOA) estimation of waves impinging a sensor array. However, the majority of the methods proposed so far only consider a known, fixed number of impinging waves, i.e., a fixed number of sources (NOS). This paper proposes a machine-learning-based estimator designed for the case when the NOS is variable and hence unknown a priori. The proposed estimator comprises a framework of single-label classifiers. Each classifier predicts if waves are present within certain randomly selected segments of the array’s field of view (FOV), resulting from discretising the FOV with a certain (FOV) resolution. The classifiers’ predictions are combined into a probabilistic angle spectrum, whereupon the NOS and the AOAs are estimated jointly by applying a probability threshold whose optimal level is learned from data. The estimator’s performance is assessed using a new performance metric: the joint AOA estimation success rate. Numerical simulations show that for low SNR (−10 dB), a low FOV resolution (2°) yields a higher success rate than a high resolution (1°), whereas the opposite applies for mid (0 dB) and high (10 dB) SNRs. In nearly all simulations, except one at low SNR and a high FOV resolution, the proposed estimator outperforms the MUSIC algorithm if the maximum allowed AOA estimation error is approximately equal to (or larger than) the FOV resolution.

Considerations of Curvature for a Near-Eye Holo-Video Display

Most 3D augmented reality, near-eye displays suffer from a low field of view. Leaky-mode lithium niobate devices are often used to steer, multiplex, or otherwise control the path of light in a system. Such devices are ideal candidates for creating such displays, and, in this paper, we demonstrate a path to increasing their view angle to 180° by curving the substrate, which will steer the output light toward the user’s eye. We also model the tradeoff between field of view, allowable interaction length, and draw distance for these curved leaky-mode devices.

Image mosaicking using improved auto-sorting algorithm and local difference-based harris features

Image mosaicking is an image processing technique which is useful for tiling images. Image Mosaicing stitches many correlated images to get a picture of a greater field of view. General-purpose cameras, which have a low field of view, can not create images with a higher field of view while mosaicking can help us achieve it. One important step in an image mosaicking framework is the auto-sorting algorithm, which is to be performed to minimize registration errors in the mosaic image. Another step in mosaicking is the detection of interest points for matching of the source images obtained after auto-sorting. However, in the presence of noisy and pseudo-periodic structures in the source images, the existing auto-sorting methods generally produce distortions in the final mosaic image. Secondly, most of the popular interest point detection algorithms do not specifically consider computational issues. So, this work mainly addresses the above-mentioned problems which are generally encountered during image mosaicking. The problem of image auto-sorting can be partially solved by adopting a phase correlation strategy. In our method, the sorting procedure is further improved by deploying the structural similarity index (SSIM) measure instead of using the phase correlation. The issue of high time complexity of conventional corner detectors is reduced by using our proposed local difference operation in place of standard Sobel edge detector. Experimental results show the efficacy of the proposed method.

Catadioptric stereo-vision system using a spherical mirror

In the computer vision field, the reconstruction of target surfaces is usually achieved by using 3D optical scanners assembled integrating digital cameras and light emitters. However, these solutions are limited by the low field of view, which requires multiple acquisition from different views to reconstruct complex free-form geometries. The combination of mirrors and lenses (catadioptric systems) can be adopted to overcome this issue. In this work, a stereo catadioptric optical scanner has been developed by assembling two digital cameras, a spherical mirror and a multimedia white light projector. The adopted configuration defines a non-single viewpoint system, thus a non-central catadioptric camera model has been developed. An analytical solution to compute the projection of a scene point onto the image plane (forward projection) and vice-versa (backward projection) is presented. The proposed optical setup allows omnidirectional stereo vision thus allowing the reconstruction of target surfaces with a single acquisition. Preliminary results, obtained measuring a hollow specimen, demonstrated the effectiveness of the described approach.

Gaze shifts during dual-tasking stair descent.

To investigate the role of vision in stair locomotion, young adults descended a seven-step staircase during unrestricted walking (CONTROL), and while performing a concurrent visual reaction time (RT) task displayed on a monitor. The monitor was located at either 3.5 m (HIGH) or 0.5 m (LOW) above ground level at the end of the stairway, which either restricted (HIGH) or facilitated (LOW) the view of the stairs in the lower field of view as participants walked downstairs. Downward gaze shifts (recorded with an eye tracker) and gait speed were significantly reduced in HIGH and LOW compared with CONTROL. Gaze and locomotor behaviour were not different between HIGH and LOW. However, inter-individual variability increased in HIGH, in which participants combined different response characteristics including slower walking, handrail use, downward gaze, and/or increasing RTs. The fastest RTs occurred in the midsteps (non-transition steps). While gait and visual task performance were not statistically different prior to the top and bottom transition steps, gaze behaviour and RT were more variable prior to transition steps in HIGH. This study demonstrated that, in the presence of a visual task, people do not look down as often when walking downstairs and require minimum adjustments provided that the view of the stairs is available in the lower field of view. The middle of the stairs seems to require less from executive function, whereas visual attention appears a requirement to detect the last transition via gaze shifts or peripheral vision.

Assessing the use of reflectance spectroscopy in determining CsCl stress in the model species Arabidopsis thaliana

Reflectance spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress, and has potential applications for use in remediation. Changes in reflectance such as that due to metal stress may occur before damage is visible, and existing studies have shown that metal stress does cause changes in plant reflectance. To further investigate the potential use of reflectance spectroscopy as a method for assessing metal stress in plants, an exploratory study was conducted in which Arabidopsis thaliana plants were treated twice weekly in a laboratory setting with varying levels (0, 0.5, or 5 mM (millimolar)) of caesium chloride (CsCl) solution, and reflectance spectra were collected every week for three weeks using an Analytical Spectral Devices FieldSpec Pro spectroradiometer with both a contact probe (CP) and a field of view (FOV) probe at 36.8 and 66.7 cm, respectively, above the plant. Plants were harvested each week after spectra collection for determination of relative water content and chlorophyll content. A visual assessment of the plants was also conducted using point observations on a uniform grid of 81 points. A mixed-effects model analysis was conducted for each vegetation index (VI) considered to determine the effects of length of treatment, treatment level, view with which spectra were acquired, and the interactions of these terms. Two-way analyses of variance (ANOVAs) were performed on the aforementioned endpoints (e.g. chlorophyll content) to determine the significance of the effects of treatment level and length of treatment. Multiple linear regression (MLR) was used to develop a predictive model for each endpoint, considering VI acquired at each view (CP, high FOV, and low FOV). Of the 14 VI considered, 8 were included in the MLR models. Contact probe readings and FOV readings differed significantly, but FOV measurements were generally consistent at each height.

Measurement of System Functions With Extended Field-of-View

The common way to obtain an image in magnetic particle imaging (MPI) is by inversion of a system function that describes the transformation between spatial distribution of the contrast agent and the measured signal. Recently, a concept of continuous motion of the field-of-view (FoV) has been introduced. In the latter, the MPI images were acquired during fast linear FoV motions. In this paper, we investigate the feasibility of more complex trajectories of the FoV in combination with adequate reconstruction. We compare the former proposed correction method with a large system function that contains the complex focus field movement. As a result, the approach to measure the complete system function yields in equal image quality for low FoV speed and slightly better image quality at the high-speed limit.

Optimization of confocal scanning laser ophthalmoscope design

Confocal scanning laser ophthalmoscopy (cSLO) enables high-resolution and high-contrast imaging of the retina by employing spatial filtering for scattered light rejection. However, to obtain optimized image quality, one must design the cSLO around scanner technology limitations and minimize the effects of ocular aberrations and imaging artifacts. We describe a cSLO design methodology resulting in a simple, relatively inexpensive, and compact lens-based cSLO design optimized to balance resolution and throughput for a 20-deg field of view (FOV) with minimal imaging artifacts. We tested the imaging capabilities of our cSLO design with an experimental setup from which we obtained fast and high signal-to-noise ratio (SNR) retinal images. At lower FOVs, we were able to visualize parafoveal cone photoreceptors and nerve fiber bundles even without the use of adaptive optics. Through an experiment comparing our optimized cSLO design to a commercial cSLO system, we show that our design demonstrates a significant improvement in both image quality and resolution.

Re-engineering the Wheatstone stereoscope

Therapeutic applications using virtual reality (VR) can deliver excellent outcomes in treating phobias1, 2 and show great promise in cases of post-traumatic stress disorder.3 VR analgesia has reduced subjective pain ratings of burn victims undergoing excruciating wound-care procedures by 30–90%.4 And functional magnetic resonance imaging scans have shown that pain-related brain activity levels in healthy individuals drop by 50–90%.5 In both these modalities, immersion is identified as a key factor.6, 7 However, head-mounted displays (HMDs) that even marginally match the capabilities of the human visual system remain extremely expensive. Stereoscopes may provide an excellent compromise at a fraction of the cost of wide field-ofview (FOV) HMDs. Progress in developing the requisite technologies—primarily high-resolution microdisplays—has been slow, and they have proved difficult to interface. Various near-eye optical systems work well for low FOV but rise rapidly in cost, complexity, and size with higher applications. This contrasts markedly with direct-view LCD displays, now commonly available in resolutions beyond high-definition television while costing less than $600. The major limitation with LCD is the 60Hz refresh rate such that two displays are required for stereoscopic use. The issue then becomes how to deploy them so that each display is viewed by only one eye. This can be accomplished with a polarizing beamsplitter,8 but also by optimizing a 150-year-old invention known as theWheatstone stereoscope. Work has been done with these scopes using cathode ray tubes,9–11 but large LCD panels offer a unique opportunity to optimize performance.12 The Wheatstone stereoscope employs two mirrors whose reflections form an overlapped image at an angle, as shown in Figure 1. Optionally, the images can be viewed through a magnifier (such as reading glasses) for greater comfort. Glasses, which also Figure 1. The Wheatstone stereoscope.

Spiral scanning with anisotropic field of view.

Spiral scanning has been used to achieve much shorter scan times than conventional techniques for a wide range of applications. The major drawback with spiral scans is blurring from off-resonant spins, which is proportional to the readout time. Blurring limits maximal spatial resolution and minimal scan time potentially achievable with spiral scanning. Anisotropic field of view is used in conventional scanning to improve image quality by matching k-space trajectory to object characteristics. Anisotropic field of view improves spatial resolution in spiral scanning without increasing scan time or blurring. The resolution improvement results from increased maximal k-space radius allowed by the lower field of view. A field of view reduction by a factor of 2 in one direction provides up to 60% resolution improvement in that direction. Reduced SNR also results from non-uniform k-space sampling.