Spatial Depth Research Articles

Activation of Mechanosensitive Ion Channels by Ultrasound.

Mechanosensitive channels (MSCs) play an important role in how cells transduce mechanical stimuli into electrical or chemical signals, which provides an interventional possibility through the manipulation of ion channel activation using different mechanical stimulation conditions. With good spatial resolution and depth of penetration, ultrasound is often proposed as the tool of choice for such therapeutic applications. Despite the identification of many ion channels as mechanosensitive in recent years, only a limited number of MSCs have been reported to be activated by ultrasound with substantial evidence. Furthermore, although many therapeutic implications using ultrasound have been explored, few offered insights into the molecular basis and the biological effects induced by ultrasound in relieving pain and accelerate tissue healing. In this review, we examined the literature, in particular studies that provided evidence of cellular responses to ultrasound, with and without the target ion channels. The ultrasound activation conditions were then summarized for these ion channels, and these conditions were related to their mode of activation based on the current biological concepts. The overall goal is to bridge the results relating to the activation of MSCs that is specific for ultrasound with the current knowledge in molecular structure and the available physiological evidence that may have facilitated such phenomena. We discussed how collating the information revealed by available scientific investigations helps in the design of a more effective stimulus device for the proposed translational purposes. Traditionally, studies on the effects of ultrasound have focused largely on its mechanical and physical interaction with the targeted tissue through thermal-based therapies as well as non-thermal mechanisms including ultrasonic cavitation; gas body activation; the direct action of the compressional, tensile and shear stresses; radiation force; and acoustic streaming. However, the current review explores and attempts to establish whether the application of low-intensity ultrasound may be associated with the activation of specific MSCs, which in turn triggers relevant cell signaling as its molecular mechanism in achieving the desired therapeutic effects. Non-invasive brain stimulation has recently become an area of intense research interest for rehabilitation, and the implication of low-intensity ultrasound is particularly critical given the need to minimize heat generation to preserve tissue integrity for such applications.

Enhancing optoacoustic mesoscopy through calibration-based iterative reconstruction

Optoacoustic mesoscopy combines rich optical absorption contrast with high spatial resolution at tissue depths beyond reach for microscopic techniques employing focused light excitation. The mesoscopic imaging performance is commonly hindered by the use of inaccurate delay-and-sum reconstruction approaches and idealized modeling assumptions. In principle, image reconstruction performance could be enhanced by simulating the optoacoustic signal generation, propagation, and detection path. However, for most realistic experimental scenarios, the underlying total impulse response (TIR) cannot be accurately modelled. Here we propose to capture the TIR by scanning of a sub-resolution sized absorber. Significant improvement of spatial resolution and depth uniformity is demonstrated over 3 mm range, outperforming delay-and-sum and model-based reconstruction implementations. Reconstruction performance is validated by imaging subcutaneous murine vasculature and human skin in vivo. The proposed experimental calibration and reconstruction paradigm facilitates quantitative inversions while averting complex physics-based simulations. It can readily be applied to other imaging modalities employing TIR-based reconstructions.

Application of subject-specific helmets for the study of human visuomotor behavior using transcranial focused ultrasound: a pilot study

Background and objectiveAs a novel non-invasive human brain stimulation method, transcranial focused ultrasound (tFUS) is receiving growing attention due to its superior spatial specificity and depth penetrability. Since the focal point of tFUS needs to be fixated precisely to the target brain region during stimulation, a critical issue is to identify and maintain the accurate position and orientation of the tFUS transducer relative to the subject's head. This study aims to propose the entire framework of tFUS stimulation integrating the methods previously proposed by the authors for tFUS transducer configuration optimization and a subject-specific 3D-printed helmet, and to validate this complete setup in a human behavioral neuromodulation study. MethodsTo find the optimal configuration of the tFUS transducer, a numerical method based on subject-specific tFUS beamlines simulation was used. Then, the subject-specific 3D-printed helmet has been applied to effectively secure the transducer at the estimated optimal configuration. To validate this tFUS framework, a common behavioral neuromodulation paradigm was chosen; the effect of the dorsolateral prefrontal cortex (DLPFC) stimulation on anti-saccade (AS) behavior. While human participants (n=2) were performing AS tasks, tFUS stimulations were randomly applied to the left DLPFC right after the fixation target disappeared. ResultsThe neuromodulation result strongly suggests that the cortical stimulation using the proposed tFUS setup is effective in significantly reducing the error rates of anti-saccades (about -10 %p for S1 and -16 %p for S2), whereas no significant effect was observed on their latencies. These observed behavioral effects are consistent with the previous results based on conventional brain stimulation or lesion studies. ConclusionsThe proposed subject-specific tFUS framework has been effectively used in human neuromodulation study. The result suggests that the tFUS stimulation targeted to the DLPFC can generate a neuromodulatory effect on AS behavior.

Arm Movement Analysis Technology of Wushu Competition Image Based on Deep Learning.

In order to improve the recognition accuracy of action poses for athletes in martial arts competitions, it is considered that a single frame pose does not have the temporal features required for sequential actions. Based on deep learning, this paper proposes an image arm movement analysis technology in martial arts competitions. The motion features of the arm are extracted from the bone sequence. Taking human bone motion information as temporal dynamic information, combined with RGB spatial features and depth map, the spatiotemporal features of arm motion data are formed. In this paper, we set up a slow frame rate channel and a fast frame rate channel to detect sequential motion of images. The deep learning model takes 16 frames from each video as samples. The softmax classifier is used to get the classification result of which action category the human action in the video belongs to. The test results show that the accuracy and recall rate of the arm motion analysis technology based on deep learning in martial arts competitions are 95.477% and 92.948%, respectively, with good motion analysis performance.

Multivariate ρ-quantiles: A spatial approach

By substituting an Lp loss function for the L1 loss function in the optimization problem defining quantiles, one obtains Lp-quantiles that, as shown recently, dominate their classical L1-counterparts in financial risk assessment. In this work, we propose a concept of multivariate Lp-quantiles generalizing the spatial (L1-)quantiles introduced by Probal Chaudhuri (J. Amer. Statist. Assoc. 91 (1996) 862–872). Rather than restricting to power loss functions, we actually allow for a large class of convex loss functions ρ. We carefully study existence and uniqueness of the resulting ρ-quantiles, both for a general probability measure over Rd and for a spherically symmetric one. Interestingly, the results crucially depend on ρ and on the nature of the underlying probability measure. Building on an investigation of the differentiability properties of the objective function defining ρ-quantiles, we introduce a companion concept of spatial ρ-depth, that generalizes the classical spatial depth. We study extreme ρ-quantiles and show in particular that extreme Lp-quantiles behave in fundamentally different ways for p≤2 and p>2. Finally, we establish Bahadur representation results for sample ρ-quantiles and derive their asymptotic distributions. Throughout, we impose only very mild assumptions on the underlying probability measure, and in particular we never assume absolute continuity with respect to the Lebesgue measure.

CORNet: Context-Based Ordinal Regression Network for Monocular Depth Estimation

Monocular depth estimation, as one of the fundamental tasks of computer vision, plays a crucial role in three-dimensional (3D) scene understanding and perception. Usually, deep learning methods recover monocular depth maps using continuous regression manners by minimizing the errors between the ground-truth depth and the predicted depth. However, fine depth features may not be fully captured through layer-by-layer coding, which is prone to low spatial resolution depth maps and insufficient details. Furthermore, it usually converges slowly and suffers from unsatisfactory results. To tackle these issues, we propose a novel model, named context-based ordinal regression network (CORNet), to reconstruct monocular depth maps in the ordinal regression manner with context information in this paper. Firstly, we put forward a novel context-based encoder with a feature transformation (FT) module to learn context information and details from inputs, and output multi-scale feature maps. Then, we design a boundary enhancement module (BEM) with a spatial attention mechanism following each operation of feature fusion, which captures boundary features in the scene to enhance the border depth. Finally, a feature optimization module (FOM) is designed to fuse and optimize the multi-scale features and boundary features to strengthen depth learning. What’s more, we introduce an ordinal weighted inference to predict depth maps from probabilities and discretization values. Experiments and results on two challenging datasets, KITTI and NYU Depth V2, demonstrate that our proposed CORNet can estimate monocular depth maps effectively and obtain superior performance in capturing geometric features over existing methods.

State of Play in Marine Soundscape Assessments

A soundscape is the recording of all sounds present in an area, creating a holistic view of the acoustic profile in an ecosystem. Studying acoustic parameters of marine soundscapes as a whole has been shown to give an indication of the health status of the location, as well as correlate to which species may be present and using the area. With the rapid innovation of technology, especially data storage and declining cost of equipment, marine soundscape research is fast increasing, and these previous limitations have been switched for computing capacity for data analysis. Here, we perform a systematic assessment of literature of marine soundscape studies, from 1978, when the first soundscape study was reported, until 2021. We identified 200 primary research studies that recorded soundscapes and captured their geographical location, depth, habitat, duration of the study, and number of sites in each study. Using this data, we summarize the state of play in marine soundscapes studies, and identify knowledge gaps in the spatial coverage, depth profiles, habitat representation and study duration. Spatially, studies are biased towards the northern hemisphere. They are also more prevalent in more easily accessible ecosystems, in order from most to least studied, in coastal (38%), pelagic (20%), tropical coral reef (17%), rocky reef (7%), polar (5.5%), seagrass meadows, oyster reef and kelp/algal forest (<5% each) areas, with zones of cold-water coral the least studied (0.3%). Continuing the trend of accessibility, studies also tended to focus on shallow ecosystems. Most recordings (68%) were conducted in the upper 50 m, with 13% in 50-200 m depths, and only 0.6% at a depth >4000 m. With anthropogenic noise and other pollution sources increasing globally, these gaps in research should be further addressed, especially as they pertain to vulnerable ecosystems, many of which are affected by global climate change and anthropogenic influences. It is crucial that marine soundscape studies continue to be developed and pursued, to establish baselines for healthy ecosystems and/or document recovery following management actions.

“Country Speech”: Regional and Temporal Linguistic Layering in Alice Munro’s Fiction

Foregrounded reports of remembered speech habits typify Alice Munro’s short fiction. In one story, the author refers to this, almost casually, as “country speech.” I will examine instances of generalized speech tags (such as “As they used to say”) to explore their relation to the creation of spatial and temporal depth in the fictional landscape. Distinctions are established between types of these foregrounded speech tags, and the category of “country speech” is extended to include a related concept of “country manners.” These combine to help create the subtly layered distinctions between place (city, country, small town) and time (decades and generations) that add texture to Munro’s narratives.

Phase-Sensitive Vibrational Sum and Difference Frequency-Generation Spectroscopy Enabling Nanometer-Depth Profiling at Interfaces

The unique physical and chemical properties of interfaces are governed by a finite depth that describes the transition from the topmost atomic layer to the properties of the bulk material. Thus, understanding the physical nature of interfaces requires detailed insight into the different structures, chemical compositions, and physical processes that form this interfacial region. Such insight has traditionally been difficult to obtain from experiments, as it requires a combination of structural and chemical sensitivity with spatial depth resolution on the nanometer scale. In this contribution, we present a vibrational spectroscopic approach that can overcome these limitations. By combining phase-sensitive sum and difference frequency-generation (SFG and DFG, respectively) spectroscopy and by selectively determining different nonlinear interaction pathways, we can extract precise depth information and correlate these to specific vibrationally resonant modes of interfacial species. We detail the mathematical framework behind this approach and demonstrate the performance of this technique in two sets of experiments on selected model samples. An analysis of the results shows an almost perfect match between experiment and theory, confirming the practicability of the proposed concept under realistic experimental conditions. Furthermore, in measurements with self-assembled monolayers of different chain lengths, we analyze the spatial accuracy of the technique and find that the precision can even reach the sub-nanometer regime. We also discuss the implications and the information content of such depth-sensitive measurements and show that the concept is very general and goes beyond the analysis of the depth profiles. The presented SFG/DFG technique offers new perspectives for spectroscopic investigations of interfaces in various material systems by providing access to fundamental observables that have so far been inaccessible by experiments. Here, we set the theoretical and experimental basis for such future investigations.

The Effect of 2D and 3D Action Video Game Interventions on Executive Functions in Male Students

Background In recent years, interest in digital games has grown significantly and at the same time a range of games in 2D and 3D has been created. While 2D games cannot give depth to objects, 3D games creates spatial depth. The growth of the gaming industry has raised concerns among some psychologists. There is still much controversy about positive or negative effects of these games on cognitive performance. Executive functions are a set of cognitive abilities that play a decisive role in one’s purposeful behavior. The present study aims to investigate the effect of 2D and 3D video games on some of these functions—flexibility, inhibition, and continuous attention—in male students aged 18–26 years. Method Forty-five male students at Persian Gulf University participated in the study. They were matched based on intelligence score and experience of playing video games. The participants were divided into three groups of 15 (two experimental groups and one control group). Participants in the two experimental groups played 2D and 3D video games over 20 sessions. They completed the Wisconsin Card Sorting Test, continuous performance test, Stroop test, and Raven intelligence test. Results Data were analyzed via covariance and the results showed that playing 2D and 3D video games positively and significantly affects inhibition and playing 3D games has a significant positive effect on flexibility. Conclusion Based on our findings, we discuss the different effects of 2D and 3D video games, in line with the study’s theoretical framework, and give suggestions for future studies.

The Effects of Silicone Enclosure Colour on the Function of Optical Sensors.

Simple SummaryImplantable optical sensing is a rapidly growing field that allows for continuous monitoring of internal organs’ physiological states. Near-infrared spectroscopy is an optical sensing technology allowing for low-cost, non-invasive, high-sensitivity measurement of tissue oxygenation and haemodynamic parameters. The colour of an optical sensor’s enclosure affects the sensor’s sensitivity, function, and ability to detect tissue vital signs. This study compared the optical properties of coloured silicone materials and related these properties to the function of silicone enclosed implantable near-infrared spectroscopy sensors. We demonstrated that sensor enclosures highly reflective to red and near-infrared light facilitated light propagation to the photodetector and increased the ability to detect the effects of cardiac pulsation and respiratory rhythm on tissue haemodynamics. In contrast, highly absorptive sensor enclosures resulted in better detection and monitoring of tissue oxygenation.The colour of the silicone enclosure of an implantable reflectance-based optical probe plays a critical role in sensor performance. Red-coloured probes that are highly reflective to near-infrared light have been found to increase photodetector power by a factor of 6 for wavelengths between 660 and 950 nm and triple the magnitude of measured cardiac pulsations compared to traditional black probes. The increase in photodetector power and cardiac pulsation magnitude is presumably due to increased spatial range resulting from a higher magnitude of superficial tissue scattering. Conversely, probes with highly absorbent colours such as black and blue result in more stable signals and are expected to have higher spatial resolution and depth of penetration.

High-speed optical resolution photoacoustic microscopy with MEMS scanner using a novel and simple distortion correction method

Optical resolution photoacoustic microscopy (OR-PAM) is a remarkable biomedical imaging technique that can selectively visualize microtissues with optical-dependent high resolution. However, traditional OR-PAM using mechanical stages provides slow imaging speed, making it difficult to biologically interpret in vivo tissue. In this study, we developed a high-speed OR-PAM using a recently commercialized MEMS mirror. This system (MEMS-OR-PAM) consists of a 1-axis MEMS mirror and a mechanical stage. Furthermore, this study proposes a novel calibration method that quickly removes the spatial distortion caused by fast MEMS scanning. The proposed calibration method can easily correct distortions caused by both the scan geometry of the MEMS mirror and its nonlinear motion by running an image sequence only once using a ruler target. The combination of MEMS-OR-PAM and distortion correction method was verified using three experiments: (1) leaf skeleton phantom imaging to test the distortion correction efficacy; (2) spatial resolution and depth of field (DOF) measurement for system performance; (3) in-vivo finger capillary imaging to verify their biomedical use. The results showed that the combination could achieve a high-speed (32 s in 2 × 4 mm) and high lateral resolution (~ 6 µm) imaging capability and precisely visualize the circulating structure of the finger capillaries.

Imaging subsurface structure over the Xiadian fault using P waves extracted from urban traffic noise

SUMMARY The imaging of subsurface structures is an essential task in subsurface engineering projects; it provides information regarding the locations of active faults and layer boundaries. Among the methods available for imaging of subsurface structures, the body wave imaging method using urban traffic noise has recently attracted attention because it permits continuous measurement at low cost in urban areas. However, because the urban traffic noise signal used for imaging on the engineering scale has characteristics that differ from the ambient noise used on the crustal scale, the conventional crustal-scale data processing workflow should be modified through systematic data analysis. In this study, traffic noise sources were systematically analysed using field data obtained over the Xiadian fault in Hebei province, China. The traffic noise signals were recorded in various patterns because of diverse incoming directions and show marked amplitude changes depending on time of recording. The overlapping signals originating from opposite directions generate spurious events and noise in the seismic interferometry images; constant processing parameters cannot respond to the large amplitude changes. In this study, to remove surface waves with markedly changing amplitude, we applied actively varying threshold values to each set of traces using the moving average of amplitude changes within the trace. In addition, the signals originating from diverse directions were separated into negative and positive slopes through the f–k filter; the interference generated by overlapping signals was minimized by applying data processing (e.g. median filtering and high amplitude removal) separately to the negative and positive slopes of each simultaneously acquired trace gather. Due to the modified data processing workflow, most spurious events were successfully suppressed in the final stacked image compared with those produced using the conventional data processing workflow, and reflections were imaged more clearly. Fault spatial locations and layer boundary depth variation in the final image obtained by the modified processing workflow were similar to those reported in previous studies.

Human-object interaction detection with depth-augmented clues

Human object interaction (HOI) detection aims to localize and classify triplets of human, object and relationship from a given image. Different from previous methods that only extract vision information in RGB images, we propose a Depth-augmented Relationship Reasoning (DRR) method that focuses on the RGB images and corresponding depth messages simultaneously. Rethinking principles of photography, we argue that RGB images discard spatial depth carrying third dimension relative distance information between instances. In light of this, we beforehand estimate the depth information for each image, yielding a corresponding depth map. Then we leverage multiple representations encoded by depth information and RGB images to enrich semantic interpretation. Subsequently, we explore a hierarchical attention strategy to fuse these semantic representations and further generate depth-augmented features, being used to reason about fine-grained human-object interactions. Extensive experiments on the benchmark datasets V-COCO, HICO-DET and HCVRD verify the effectiveness of our method and demonstrate the importance of spatial depth information for HOI.

A Wide Field-of-View Light-Field Camera with Adjustable Multiplicity for Practical Applications.

The long-fascinated idea of creating 3D images that depict depth information along with color and brightness has been realized with the advent of a light-field camera (LFC). Recently advanced LFCs mainly utilize micro-lens arrays (MLAs) as a key component to acquire rich 3D information, including depth, encoded color, reflectivity, refraction, occlusion, and transparency. The wide field-of-view (FOV) capability of LFCs, which is expected to be of great benefit for extended applications, is obstructed by the fundamental limitations of LFCs. Here, we present a practical strategy for the wide FOV-LFC by adjusting the spacing factor. Multiplicity (M) is the inverse magnification of the MLA located between the image plane and the sensor, which was introduced as the overlap ratio between the micro-images. M was adopted as a design parameter in several factors of the LFC, and a commercial lens with adjustable FOV was used as the main lens for practicality. The light-field (LF) information was evaluated by considering the pixel resolution and overlapping area in narrow and wide FOV. The M was optimized for narrow and wide FOV, respectively, by the trade-off relationship between pixel resolution and geometric resolution. Customized wide FOV-LFCs with different M were compared by spatial resolution test and depth information test, and the wide FOV-LFC with optimized M provides LF images with high accuracy.

Multi-Scale translation method from SAR to optical remote sensing images based on conditional generative adversarial network

ABSTRACT Synthetic aperture radar (SAR) has all-weather and all-day observation capabilities and a certain ability to penetrate the surface; therefore, it has unique advantages in many aspects, which other remote sensing methods cannot achieve. However, owing to imaging principles, the interpretation of SAR images is complicated. Therefore, converting SAR images into optical remote sensing images is one method of SAR image interpretation. Therefore, this paper proposes an improved conditional generative adversarial network (cGAN) that includes a generator based on the encoder-decoder structure of the swin transformer feature extraction module. The generator uses a spatial pyramid structure and multi-scale depth feature extraction structure to extract the SAR image features at different scales. A multi-scale discriminator was used to discriminate images on different scales. The introduction of feature matching loss makes the discriminator’s feedback to the generator richer and uses perceptual loss based on VGGNet to evaluate the image quality in depth. A series of experiments verified the effectiveness of the method in this study and proved the potential of the transformer structure in the field of SAR image translation. The method presented in this paper has obvious advantages and can translate SAR images into optical remote sensing images.

Nuclear two point correlation functions on a quantum computer

The calculation of dynamic response functions is expected to be an early application benefiting from rapidly developing quantum hardware resources. The ability to calculate real-time quantities of strongly-correlated quantum systems is one of the most exciting applications that can easily reach beyond the capabilities of traditional classical hardware. Response functions of fermionic systems at moderate momenta and energies corresponding roughly to the Fermi energy of the system are a potential early application because the relevant operators are nearly local and the energies can be resolved in moderately short real time, reducing the spatial resolution and gate depth required. This is particularly the case in quasielastic electron and neutrino scattering from nuclei, a topic of great interest in the nuclear and particle physics communities and directly related to experiments designed to probe neutrino properties. In this work we use current quantum hardware and error mitigation protocols to calculate response functions for a highly simplified nuclear model through calculations of a 2-point real time correlation function for a modified Fermi-Hubbard model in two dimensions with three distinguishable nucleons on four lattice sites.

Optical fiber-based handheld polarized photoacoustic computed tomography for detecting anisotropy of tissues.

Photoacoustic computed tomography (PACT) is a fast-developing biomedical imaging modality and has immense potential for clinical translation. It utilizes laser excitation and acoustic detection to achieve high spatial resolution and considerable imaging depth in biological tissues. Current PACT primarily treats the absorption coefficient of tissues as a scalar variable while reconstructing the image, which limits its use for anisotropic evaluation of the tissues. Thus, by incorporating polarized imaging methods to evaluate anisotropy, applications of PACT can be further enhanced. So far, dichroism-sensitive PACT has been suggested for polarization detection of biological tissues. However, this approach is unsuitable for intraoperative imaging, since high-power spatial light is needed for excitation, which is dangerous and inconvenient to operate. Thus, there is a need to develop a polarized PACT system suitable for clinical use. Herein, we have proposed a specially designed handheld polarized PACT (HP-PACT) system, which was designed to promote intraoperative anisotropy detection of biological tissues. Excitation light was delivered by an optical fiber and reshaped by a compact set of lenses at the output end of the optical fiber. A polarizer was applied to generate linearly polarized light, and the polarization direction was adjusted by simply rotating the half-wave plate. Photoacoustic imaging (PAI) using excitation with several different polarization directions was carried out. Optical axes and the structure of the anisotropic objects were obtained using the principle of polarization detection with the PAI. We experimentally demonstrated the performance of HP-PACT by imaging both the polarized and unpolarized plastic films. The results showed that HP-PACT can successfully detect the direction of the optical axes of polarized plastic films and has the ability to image at different depths. When linearly polarized light with different polarization directions was used as excitation, PAI studies on a highly anisotropic bovine tendon and relatively low anisotropic mouse leg showed the structural differences between the 2 tissues. The quantified degrees of anisotropy of the bovine tendon and mouse legs were 0.6 and 0.3, respectively. The proposed HP-PACT is able to determine the anisotropic substances' optical axes and distinguish anisotropic substances from isotropic ones. Thus, HP-PACT has the potential for intraoperative diagnosis and treatment of anisotropic tissues, including nerves and tendons.

Differential evolution method to find optimal location of a single-element transducer for transcranial focused ultrasound therapy

Background and objectiveFocused ultrasound (FUS) has been receiving growing attention as a noninvasive brain stimulation tool because of its superior spatial specificity and depth penetrability. However, the large mismatch of acoustic properties between the skull and water can disrupt and shift the acoustic focus in the brain. In this paper, we present a numerical method to find the optimal location of a single-element FUS transducer, which creates focus on the target region. MethodsThe score function, representing the superposition of acoustic waves according to the relative phase difference and transmissibility, was defined based on time-reversal invariance of acoustic waves and depending on the spatial location of the transducer. The optimal location of the transducer was then determined using a differential evolution algorithm. To assess the proposed method, we conducted a forward simulation and compared the resulting focal location to the desired target point. We also performed experimental validation by measuring the acoustic pressure field through an ex vivo human skull in a water tank. ResultsThe numerical results indicated that the score function had a positive proportional relationship with the acoustic pressure at the target. Moreover, for the optimized transducer location, both the numerical and experimental results showed that the normalized acoustic pressure at the target was higher than 0.9. ConclusionsIn this study, we developed an optimization method to place a single-element transducer that effectively transmits acoustic energy to the targeted region in the brain. Our numerical and experimental results demonstrate that the proposed method can provide an optimal transducer location for safe and efficient FUS treatment.

A Workflow for Three-Dimensional Reconstruction and Quantification of the Monkey Optic Nerve Head Vascular Network.

A comprehensive characterization of the three-dimensional (3D) vascular network of the optic nerve head (ONH) is critical to understanding eye physiology and pathology. Current in vivo imaging technologies, however, do not have simultaneous high spatial resolution and imaging depth to resolve the small vessels deep within the ONH. We describe a workflow for the 3D reconstruction and quantitative morphological analysis of the ONH vasculature. The vessels of a normal monkey ONH were perfusion labeled. Serial cryosections of the ONH were imaged using fluorescence microscopy (FM) and instant polarized light microscopy (IPOL) to visualize the labeled vessels and label-free collagen, respectively. The IPOL images were registered and used to form a stack of FM images from which the vessels were segmented and skeletonized to reconstruct the 3D vascular network. The network consisted of 12,966 vessel segments, 7989 branching points, and 1100 terminal points at the boundaries. For each vessel segment, we measured its length, tortuosity, inclination (θ), and polar orientation (φ). The length followed a lognormal distribution, whereas the distribution of the tortuosity followed an exponential decay. The vessels were mainly oriented toward the coronal plane (θ = 90 deg). For orientation, there were nearly as many vessels aligned circumferentially (φ = 90 deg) and radially (φ = 0 deg). Our results demonstrate the workflow for 3D eye-specific reconstruction and quantification of the monkey ONH vascular network. This is a critical first step to analyze the blood flow and oxygenation within the ONH, which will help understand the role of vascular dysfunction in glaucoma.