Two-Dimensional Photoacoustic/Ultrasonic Endoscopic Imaging Based on a Line-Focused Transducer

Existing acoustic-resolution photoacoustic/ultrasonic endoscopy (PA/USE) generally employs a point-focused transducer for ultrasound detection, which is only sensitive in its focal region, thus the lateral resolution and sensitivity drop dramatically when the targets move far from its focus. Even if a dynamic focusing algorithm is applied, the sensitivity out of the transducer focus is still much lower than that in the focus in ultrasonic imaging mode. In this work, we propose an acoustic-resolution PA/USE with a line-focused transducer to realize automatic focusing for the first time. In comparison to a point-focused transducer, the line-focused transducer emits a more uniform sound field, causing the original signal intensity and signal-to-noise ratio (SNR) of the front and rear targets to be closer in the radial direction, which is beneficial for improving target signal uniformity in ultrasonic imaging. Simultaneously, we improved the resolution of the defocus area by modifying a prior work of back-projection (BP) reconstruction algorithm typically used in point-focused transducer based PAE and applying it to line-focused PA/USE. This combined approach may significantly enhance the depth of field of ultrasonic imaging and the resolution of the defocus zone in PA/US imaging, compared to the conventional method. Sufficient numerical simulations and phantom experiments were performed to verify this method. The results show that our method can effectively improve the lateral resolution in the image’s defocused region to achieve automatic focusing and perfectly solve the defect of the target signal difference in the far-focus region in ultrasonic imaging, while also enhancing the image SNR and contrast. The proposed method in this paper lays foundations for the realization of photoacoustic/ultrasonic combined endoscopy with enhanced lateral resolution and depth of field, which can potentially benefit a many of biomedical applications.

A library for fMRI real-time processing systems in python (RTPSpy) with comprehensive online noise reduction, fast and accurate anatomical image processing, and online processing simulation

We introduce a python library for real-time fMRI (rtfMRI) data processing systems, Real-Time Processing System in python (RTPSpy), to provide building blocks for a custom rtfMRI application with extensive and advanced functionalities. RTPSpy is a library package including 1) a fast, comprehensive, and flexible online fMRI denoising pipeline comparable to offline processing, 2) utilities for fast and accurate anatomical image processing to define a target region on-site, 3) a simulation system of online fMRI processing to optimize a pipeline and target signal calculation, 4) interface to an external application for feedback presentation, and 5) a boilerplate graphical user interface (GUI) integrating operations with RTPSpy library. Since online fMRI data processing cannot be equivalent to offline, we discussed the limitations of online analysis and their solutions in the RTPSpy implementation. We developed a fast and accurate anatomical image processing script with fast tissue segmentation (FastSeg), image alignment, and spatial normalization, utilizing the FastSurfer, AFNI, and ANTs. We confirmed that the FastSeg output was comparable with FreeSurfer, and could complete all the anatomical image processing in a few minutes. Thanks to its highly modular architecture, RTPSpy can easily be used for a simulation analysis to optimize a processing pipeline and target signal calculation. We present a sample script for building a real-time processing pipeline and running a simulation using RTPSpy. The library also offers a simple signal exchange mechanism with an external application. An external application can receive a real-time neurofeedback signal from RTPSpy in a background thread with a few lines of script. While the main components of the RTPSpy are the library modules, we also provide a GUI class for easy access to the RTPSpy functions. The boilerplate GUI application provided with the package allows users to develop a customized rtfMRI application with minimum scripting labor. Finally, we discussed the limitations of the package regarding environment-specific implementations. We believe that RTPSpy is an attractive option for developing rtfMRI applications highly optimized for individual purposes. The package is available from GitHub (https://github.com/mamisaki/RTPSpy) with GPL3 license.

Virtual Reality Interactive Method and Device Based on Wireless Communication Tracking

Virtual reality is a computer system that creates a virtual world and then experiences through multiple senses. It is generated by a computer and stimulated by perception systems such as hearing, vision, touch, taste, and smell, providing users with a personal experience. Human-computer interaction is one of the core technologies of virtual reality. Wireless communication is the transmission of communications over long distances between multiple nodes without propagation through conductors or cables and can be carried out using radios, radios, etc. Wireless communication includes a variety of fixed, mobile, and portable applications such as two-way radios, mobile phones, personal digital assistants, and wireless networks. Other examples of radio wireless communication are GPS, garage door remotes, wireless mice, etc. Most wireless communication technologies use radio, including Wi-Fi with distances of just a few meters, but also deep space networks that communicate with Voyager 1 and distances of over millions of kilometers. With the continuous development of sensors and other supporting hardware facilities, the current development of human-computer interaction in virtual reality has made rapid progress. In the research to be conducted in this article, the virtual reality system used in this article cleverly integrates the three characteristics of immersion, interactivity, and conception, so that the experimenter can obtain more realistic data in comparison. To this end, this article first gives a general introduction to virtual reality technology and wireless communication tracking technology and then explains how to use wireless communication tracking technology to make the virtual reality interactive system smoother and smoother, as well as the introduction of its devices. This article explores and analyzes the possible or existing problems of wireless communication tracking technology in virtual reality interaction, hoping to contribute to the wider application of wireless communication tracking technology in virtual reality interaction. The positioning experiment on the wireless mobile signal identification points can be obtained. Among the 40 sensor nodes that are randomly deployed, when the interval of adjusting the mobile signal identification point to broadcast the current position information is 5 s, the average positioning error of the node is about 1.5 m; when the interval is 3 s, the average positioning error of the node is about 1.76 m. It can be seen that the positioning error of the node increases as the interval between the mobile signal identification points increases, which is consistent with the simulation detection result. When the node position of the target signal identification point is chosen to calculate does not just stay on the node communication circle, it introduces a certain localization distance difference, and the further the target signal identification point is from the position of the signal circle, the greater the error. Irregularity of RSS due to environmental changes analyzes the maximum error and provides the factors influencing the error and analyzing the maximum error and provide the factors that influence it.

METHOD OF EXPANDING THE DYNAMIC RANGE OF MEASURING SIGNALS OPTICAL LOCATORS

A method for broadening the dynamic range of signals in optical locators of a portable complex has been developed, which allows increasing sensitivity and perform effective spatial and spectral selection of signals against noise, what affects the quality of the detecting and tracking aerodynamic objects task. An assessment of the possibility of object detecting in different interference situations, i.e. the selection of the target signal from noise, background or internal, depending on the method of signal processing.

Archetypal Analysis and Structured Sparse Representation for Hyperspectral Anomaly Detection

Hyperspectral images (HSIs) often contain pixels with mixed spectra, which makes it difficult to accurately separate the background signal from the anomaly target signal. To mitigate this problem, we present a method that applies spectral unmixing and structure sparse representation to accurately extract the pure background features and to establish a structured sparse representation model at a sub-pixel level by using the Archetypal Analysis (AA) scheme. Specifically, spectral unmixing with AA is used to unmix the spectral data to obtain representative background endmember signatures. Moreover the unmixing reconstruction error is utilized for the identification of the target. Structured sparse representation is also adopted for anomaly target detection by using the background endmember features from AA unmixing. Moreover, both the AA unmixing reconstruction error and the structured sparse representation reconstruction error are integrated together to enhance the anomaly target detection performance. The proposed method exploits background features at a sub-pixel level to improve the accuracy of anomaly target detection. Comparative experiments and analysis on public hyperspectral datasets show that the proposed algorithm potentially surpasses all the counterpart methods in anomaly target detection.

Finding an optimal dictionary of different wavelet types using sparse modeling to denoise ECG signal

Sparse signal modeling often reconstructs a signal with few atoms from a pre-defined dictionary. Hence the choice of wavelet dictionary that represents the sparsity of the target signal is crucial in sparse modeling approach. The challenge of finding an optimal dictionary of different wavelet types using sparse denoising model (SDM) to denoise ECG signal is investigated in this work. A method of finding an optimal wavelet dictionary from a set of orthogonal wavelet sub-dictionaries by the means of the best correlation with ECG signal, is developed. The highly correlated sub-dictionaries from three wavelet dictionaries, namely daubechies, symlets, coiflets and discrete cosine transform are combined to construct an overcomplete dictionary. The weight of Akaike’s information criterion and the signal-to-noise ratio improvement are considered as a criterion to evaluate the performance of the proposed SDM. The results indicate that multi-wavelet dictionary of different types is highly sparse and efficient in denoising the target signal, e.g., ECG.

CRP Detection Using Gold Nanosensors – Effect of Layer Thickness and Immobilization Chemistry

The immobilization of a capture molecule represents a crucial step for effective usage of gold nanoparticles in localized surface plasmon resonance (LSPR)-based bioanalytics. Depending on the immobilization method used, the resulting capture layer is of varying thickness. Thus, the target binding event takes place in different distances to the gold surface. Using the example of a C-reactive protein (CRP) immunoassay, different immobilization methods were tested and investigated with regard to their resulting target signal strength. The dependency of the target signal on the distance to the gold surface was investigated utilizing polyelectrolyte bilayers of different thickness. It could be experimentally demonstrated how much the LSPR-shift triggered by a binding event on the gold nanoparticles decreases with increasing distance to the gold surface. Thus, the sensitivity of an LSPR assay is influenced by the choice of immobilization chemistry.