FS-2001多路射线监测仪的研制

FS-2001型多路射线监测仪是一种智能化多探头的电离辐射剂量监测仪器，该仪器有四路相对独立的测量系统，用于辐照场工作场所的射线监测并具有声光报警功能，同时能够输出控制信号，控制安全连锁装置，保证生产过程，操作人员的安全。     

4×155Mb／s频分复用（FDM）光纤通信系统的研究

报道了一个无故障工作时间大于２４小时的四路１５５Ｍｂ／ｓ频分复用（ＦＤＭ）光纤通信系统，实测系统误码率优于０×１０（－１４）。系统接收机包括解复用光滤波器，接收机灵敏度优于－３０ｄＢｍ（ＢＥＲ＝１×１０（－９），频道间距为０．１ｎｍ，四路ＦＤＭ信号－２０ｄＢ的总谱宽为０．７ｎｍ。系统采用国产ＤＦＢ激光器为光源，实际光纤传输距离１８ｋｍ。系统全部实现了脱离光学平台的模块化结构，在长期的系统实验中显示了优良的稳定性。这一成果为ＦＤＭ在光纤传输接入网中的进一步实用化开发铺平了道路。     

FS-2001多路射线监测仪的研制

FS -2 0 0 1型多路射线监测仪是一种智能化多探头的电离辐射剂量监测仪器 ,该仪器有四路相对独立的测量系统 ,用于辐照场工作场所的射线监测并具有声光报警功能 ,同时能够输出控制信号 ,控制安全连锁装置。保证生产过程、操作人员的安全。     

调频信号发射超声成像的参数优化与成像实验

研究调频信号发射超声成像中影响成像质量的各种参数,提高现有超声图像的信号噪声比.用仿真计算和声学实验来研究不同调频超声信号发射参数下的成像质量.增加超声发射能量,提高图像的信号噪声比;同时,采用相关算法对接收的超声信号解码,保证图像的轴向精度不会下降.优化了调频信号发射超声成像的发射参数,并得到了仿体的B型超声图像,此图像的质量优于传统成像方法的图像质量.该成像方法能够提高超声图像的信号噪声比,尤其是提高超声衰减严重的深部组织图像的信号噪声比.     

基于AD590四路巡检数字温度计的设计

本文介绍了一种可对四路温度进行数字显示的温度巡检仪,其包含:温度信号检测及转换部分、四路巡检部分、A/D转换及数字显示三大部分。该系统的工作原理为:AD590传感器将温度信号转化成电流信号,经放大电路变换成与温度成线性关系的电压信号,再由数字控制电路送到A/D转换器,最后通过数字显示器显示出测量的温度.其测量范围为-55℃~150℃,具有实用性强、可靠性高、测量精度高等特点。     

基于ARM的超声洁牙机检测系统设计

介绍一种新型的基于ARM嵌入式技术开发的超声洁牙机检测系统。该系统以PHILIPS公司LPC2132芯片为核心，集成温度、压力、频率和振幅模拟放大电路，步进电机驱动单元。硬件平台上移植μC／OS-Ⅱ嵌入式实时操作系统，实现多路信号的实时采集与显示。此系统精度高，可靠性好，可以满足用户对超声洁牙机检测的要求，具有很好的应用前景。     

基于超声图像特征的肝硬化分析系统

文章首先研究了肝脏M型超声图像和B型超声图像的特征提取，提取了肝脏M型超声图像的运动包络、相隔一定时间的A型扫描线对的相关特征系数以及肝脏B型超声图像的共25个特征参数。在已提取的特征参数中，用特征融合的方法筛选出对肝硬化最敏感的特征组，并利用这20个参数的Fisher判据建立了基于超声图像特征的肝硬化无损自动分析系统。对临床43例的应用表明：该定量分析系统对肝硬化的诊断具有良好的效果。     

多分辨率的自动MRI图像配准

在功能磁共振成像过程中，头部运动会造成相同层面图像在空间位置上的不匹配，带来严重的伪差或导致功能信号的丢失。因此，在对ＭＲＩ图像进行检验之前，必须将其与一个标准或参考图像配准，本文提出了一种多分辨率的最优化算法，由于ＲＭＲＩ图像被表征成为连续形式且多分辨率的数据结构图像具有平滑作用，该算法良好的配准精度和抗噪声能力，另外，算法的大部分叠代是在低分辨率情况下进行，且在高分辨率情况下，最优化方法具有委     

多路温湿度变送器自动测量装置的研制

针对目前国内实验室校准温湿度变送器时,都需要用多台仪表及直流稳压电源进行组合测量的缺点,设计了一体化温湿度变送器自动测量装置。该装置电路系统基于STM32F103微控制器和ADS1256ADC芯片为核心研究设计多路信号采样测量控制系统;上位机应用程序采用LABVIEW开发平台与数据库技术设计实现。可以同时测量34路变送器,实现变送器自动供电、信号类型自动识别、自动数据处理与显示存储、无线数据传输、自动生成测量报告以及仪器自动校准等功能。该装置的电流、电压采样精度高达0.05%,具有测量效率高、成本低、智能化程度高等特点。     

B超图像的计算机实时成像研究

早在50年代前期，超声就被研究并作为医学上的一种诊断工具。随着超声诊断技术的发展，超声医学诊断成为一门专门的医学诊断技术，并形成一个独立的分支。B超图像是由医学B型超声扫描仪(Ultrasound—B-mode Scanner)采用脉冲回波法对被测物体进行扫描，通过对所得的回波数据重建而形成的一类医学图像，它的主要成像原理是运用超声在人体组织中传播特性(速度、反射率、吸收率等)的不同，将其转化为一定的可显信号，在显示器上反映出来。文章对该类图像在计算机上重建的算法进行了研究，对各种算法分析、比较，最后提出比较合理的适应于计算机上实时重建B超图像的算法。     

高强度聚焦超声热疗中组织损伤的一种监测方法

用特定频率和功率的高强度聚焦超声（HIFU）照射离体猪肉组织,研究了焦点区域的B超图像变化与HIFU导致的组织损伤之间的关系,并研究了M超信号变化和温度的相关性。结果表明：逐渐增加HIFU照射次数,焦点区域组织变性,B超图像发生明显改变。靶区内灰度超过设定的阈值的区域面积增大,区域内灰度升高,两者均与照射次数成近似线性关系;模拟加热实验中M超信号也随温度升高而变化,其变化较B超更显著。与以往的方法相比,实验系统可以实时地检测到组织损伤的程度和范围,提供了一种新的可视化的HIFU治疗实时监测方法。     

Influence of luminance and resolution on the perceived quality of black-and-white images on soft displays

Abstract

The perceived quality of an image displayed on a computer monitor depends on a number of different factors that can affect viewers' preferences. Two of these are the luminance of the monitor display and the resolution of the image. The effect of luminance is of interest for applications such as on-line access of images where the computer displays used for viewing these images could have different luminance settings. A relationship between cathode-ray tube (CRT) display luminance and resolution has been shown in previous studies. It was therefore interesting to investigate whether there is a relationship between image resolution and CRT display luminance on perceived image quality. Image resolution is related to the image file size, which is an important factor for applications such as on-line access of images. This work used a CRT display to study the effect of the above-mentioned factors on the perceived quality of the displayed image. Three sets of black-and-white images, each set with a different resolution, were presented to observers at three brightness settings of the computer monitor. Results are discussed regarding the effect of monitor display luminance and image resolution on perceived image quality and the interaction between them. Evaluation of results is further extended to the influence of the different backgrounds of the images. The scene content of the images was also shown to affect the viewers' judgement.     

Generation of self-reproducing fractal patterns using a multiple imaging system with feedback

Abstract

We present a simple optical system for producing self-similar fractal patterns. The key component comprises three adjacent lenses, which form multiple images of a pattern displayed on a monitor. The images are recorded by a camera and displayed as the new pattern on the monitor. Iteration of this process results in an approximation to a self-similar fractal pattern which is independent of the starting image.     

Shadow Detection and Removal From Photo-Realistic Synthetic Urban Image Using Deep Learning

Recently, virtual reality technology that can interact with various data is used for urban design and analysis. Reality, one of the most important elements in virtual reality technology, means visual expression so that a person can experience threedimensional space like reality. To obtain this realism, real-world data are used in the various fields. For example, in order to increase the realism of 3D modeled building textures real aerial images are utilized in 3D modelling. However, the aerial image captured during the day can be shadowed by the sun and it can cause the distortion or deterioration of image. To resolve this problem, researches on detecting and removing shadows have been conducted, but the detecting and removing shadow is still considered as a challenging problem. In this paper, we propose a novel method for detecting and removing shadows using deep learning. For this work, we first a build a new dataset of photo-realistic synthetic urban data based on the virtual environment using 3D spatial information provided by VWORLD. For detecting and removing shadow from the dataset, firstly, the 1-channel shadow mask image is inferred from the 3-channel shadow image through the CNN. Then, to generate a shadow-free image, a 3-channel shadow image and a detected 1-channel shadow mask into the GAN is executed. From the experiments, we can prove that the proposed method outperforms the existing methods in detecting and removing shadow.     

Characterization of Wire Rope Defects with Gray Level Co-occurrence Matrix of Magnetic Flux Leakage Images

Magnetic flux leakage (MFL) techniques are used extensively for non-intrusively detecting and characterizing wire rope defects. Traditionally, MFL signals are captured with induction coil sensors. However, the output of coil sensors is related to the wire rope speed, and they can only provide the axial distribution along the wire rope. Hall sensors array are designed due to the limitation of coil sensors. In this paper, a Hall sensors array was designed to capture the MFL signals both axially and circumferentially. 30-channel data from Hall sensors are processed to compose a MFL image. A digital image process technique is introduced to preprocess the MFL image, the MFL images from different types of defects show different texture characteristics. Gray level co-occurrence matrix is utilized for feature extraction of the texture in the MFL image. Five typical eigenvalues (contrast, correlation, energy, homogeneity and entropy) are used as the inputs of back propagation (BP) networks. After training with typical samples, the BP networks show good performance in the quantitative recognition of different defects. The result of this work shows that texture analysis method for MFL image is suitable for feature extraction and quantitative detection of wire rope defects.     

An electron spectrum and profile monitor for the UK free electron laser

A versatile electron spectrum monitor has been developed for the UK free electron laser project. The monitor uses secondary emission from 96 tungsten foils and microprocessor-controlled sampling electronics to produce a high-resolution electron energy spectrum. A 30-channel prototype is currently operating as a beam profile monitor and has been extensively used in emittance measurements at the Kelvin Laboratory linac.     

Extracting one-dimensional wavelet features with a diffractive optical inner-product transform

A diffractive optical element (DOE) that performs a wavelet transform on one-dimensional signals is presented. The DOE performs an inner product between the input image and a set of wavelet basis functions. The input image is displayed in a spatial light modulator. It is constructed from a one-dimensional signal that is spread over the second dimension. Simulated results obtained by the use of elementary one-dimensional signals are presented.     

Binary zone-plate array for a parallel joint transform correlator applied to face recognition

Taking advantage of small aberrations, high efficiency, and compactness, we developed a new, to our knowledge, design procedure for a binary zone-plate array (BZPA) and applied it to a parallel joint transform correlator for the recognition of the human face. Pairs of reference and unknown images of faces are displayed on a liquid-crystal spatial light modulator (SLM), Fourier transformed by the BZPA, intensity recorded on an optically addressable SLM, and inversely Fourier transformed to obtain correlation signals. Consideration of the bandwidth allows the relations among the channel number, the numerical aperture of the zone plates, and the pattern size to be determined. Experimentally a five-channel parallel correlator was implemented and tested successfully with a 100-person database. The design and the fabrication of a 20-channel BZPA for phonetic character recognition are also included.     

Non-Contact Physiological Measurement System for Wearing Masks During the Epidemic

Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory rate, and forehead temperature for people wearing masks due to the pandemic. Using the green (G) minus red (R) signal in the RGB image, the region of interest (ROI) is established in the forehead and nose bridge regions. The photoplethysmography (PPG) waveforms of the two regions are obtained after the acquired PPG signal is subjected to the optical flow method, baseline drift calibration, normalization, and bandpass filtering. The relevant parameters in Deep Neural Networks (DNN) for the regression model can correctly predict the heartbeat and blood pressure. In addition, the temperature change in the ROI of the mask after thermal image processing and filtering can be used to correctly determine the number of breaths. Meanwhile, the thermal image can be used to read the temperature average of the ROI of the forehead, and the forehead temperature can be obtained smoothly. The experimental results show that the above-mentioned physiological signals of a subject can be obtained in 6-s images with the error for both heart rate and blood pressure within 2%~3% and the error of forehead temperature within ±0.5°C.     

Acoustic radiation force impulse imaging of myocardial radiofrequency ablation: initial in vivo results

Acoustic radiation force impulse (ARFI) imaging techniques were used to monitor radiofrequency (RF) ablation of ovine cardiac tissue in vivo. Additionally, ARFI M-mode imaging methods were used to interrogate both healthy and ablated regions of myocardial tissue. Although induced cardiac lesions were not visualized well in conventional B-mode images, ARFI images of ablation procedures allowed determination of lesion location, shape, and relative size through time. The ARFI M-mode images were capable of distinguishing differences in behavior through the cardiac cycle between healthy and damaged tissue regions. As conventional sonography is often used to guide ablation catheters, ARFI imaging, which requires no additional equipment, may be a convenient modality for monitoring lesion formation in vivo.