An accurate method for correction of head movement in PET

A method is presented to correct positron emission tomography (PET) data for head motion during data acquisition. The method is based on simultaneous acquisition of PET data in list mode and monitoring of the patient's head movements with a motion tracking system. According to the measured head motion, the line of response (LOR) of each single detected PET event is spatially transformed, resulting in a spatially fully corrected data set. The basic algorithm for spatial transformation of LORs is based on a number of assumptions which can lead to spatial artifacts and quantitative inaccuracies in the resulting images. These deficiencies are discussed, demonstrated and methods for improvement are presented. Using different kinds of phantoms the validity and accuracy of the correction method is tested and its applicability to human studies is demonstrated as well.     

Online removal of eye movement and blink EEG artifacts using a high-speed eye tracker

A novel approach is presented for using an eye tracker-based reference instead of EOG for methods that require an EOG reference to remove ocular artifacts (OA) from EEG. It uses a high-speed eye tracker and a new online algorithm for extracting the time course of a blink from eye tracker images to remove both eye movement and blink artifacts. It eliminates the need for EOG electrodes attached to the face, which is critical for practical daily applications. The ability of two adaptive filters (RLS and H^ ) to remove OA is measured using: 1) EOG; 2) frontal EEG only (fEEG); and 3) the eye tracker with frontal EEG (ET + fEEG) as reference inputs. The results are compared for different eye movements and blinks of varying amplitudes at electrodes across the scalp. Both the RLS and H^ methods were shown to benefit from using the proposed eye tracker-based reference (ET + fEEG) instead of either an EOG reference or a reference based on frontal EEG alone.     

A model-based objective evaluation of eye movement correction in EEG recordings

We present a method to quantitatively and objectively compare algorithms for correction of eye movement artifacts in a simulated ongoing electroencephalographic signal (EEG). A realistic model of the human head is used, together with eye tracker data, to generate a data set in which potentials of ocular and cerebral origin are simulated. This approach bypasses the common problem of brain-potential contaminated electro-oculographic signals (EOGs), when monitoring or simulating eye movements. The data are simulated for five different EEG electrode configurations combined with four different EOG electrode configurations. In order to objectively compare correction performance for six algorithms, listed in Table III, we determine the signal to noise ratio of the EEG before and after artifact correction. A score indicating correction performance is derived, and for each EEG configuration the optimal correction algorithm and the optimal number of EOG electrodes are determined. In general, the second-order blind identification correction algorithm in combination with 6 EOG electrodes performs best for all EEG configurations evaluated on the simulated data.     

浅谈头戴式眼动仪的设计

本文简单的介绍集成了头戴式显示引导,红外发光照明,蓝牙通讯等技术的头戴式眼动仪。并利用瞳孔定位算法和头戴式眼睛操控装置,用户能通过眼球的注视对建立的虚拟界面进行操作,对于帮助高位截瘫、肌肉萎缩、中风等残疾人有重大意义。     

Classification of artifactual EEG signal and detection of multiple eye movement artifact zones using novel Time-amplitude algorithm

Electroencephalogram (EEG) signal has numerous applications in the field of medical science. It is used to diagnose many of the abnormalities, disorders, and diseases related to the human brain. The EEG signal contaminated with ocular artifacts makes it very difficult for analysis and diagnosis. This paper includes work on classification of artifactual/non-artifactual EEG time series and perfect detection of eye movement (EM) artifact contaminated EEG signal along with multiple EM artifactual zones in the same time series. Artificial Neural Network classifier in a simple perceptron model without hidden layer is used for the identification. This study presents a newly developed, simple, robust, and computationally fast statistical Time-Amplitude algorithm. By the application of novel Time-Amplitude algorithm on identified signal, the EM artifactual EEG signal along with multiple zones is automatically detected and marked accurately. Such robust, efficient, real-time and simple algorithm is not ever designed and used for ocular artifact detection by any author. The ROC analysis gives accuracy of the ANN model for classifying the presence of artifacts in the EEG data, which is 97.50 %. The time elapsed for executing the Time-Amplitude algorithm for automatic detection of EM artifact is very less (4.30 msec.) compared to DWT with Haar. It has the capability to detect multiple EM artifactual zones, in the same time, for the montage of 8-second EEG.     

An improved algorithm for 2-D translational motion artifact correction

The quality of magnetic resonance imaging systems has improved to the point that motion is a major limitation in many examinations. Translational motion in the imaging plane causes the phase of the data to be corrupted. An algorithm using computer post-processing is proposed to correct the phase of the data, and hence remove the artifact. This algorithm has superior convergence properties to an earlier algorithm, which is achieved by incorporating additional prior information specific to the situation. The algorithm is verified using a Shepp and Logan phantom with simulated motion in the imaging plane. It is shown that the algorithm can correct both periodic and random motion, and that the algorithm is not significantly degraded when noise is present.     

Motion artifact correction for MR images based on convolutional neural network

Magnetic resonance imaging (MRI) is a common way to diagnose related diseases. However, the magnetic resonance (MR) images are easily defected by motion artifacts in their acquisition process, which affects the clinicians'' diagnosis. In order to correct the motion artifacts of MR images, we propose a convolutional neural network (CNN)-based method to solve the problem. Our method achieves a mean peak signal-to-noise ratio (PSNR) of (35.212±3.321) dB and a mean structural similarity (SSIM) of 0.974 ± 0.015 on the test set, which are better than those of the comparison methods.     

Motion artifact correction in MRI using generalized projections

An algorithm that suppresses translational motion artifacts in magnetic resonance imaging (MRI) by using post processing on a standard spin-warp image is presented. It is shown that translational motion causes an additional phase factor in the detected signal and that this phase error can be removed using an iterative algorithm of generalized projections. The method has been tested using computer simulations and it successfully removed most of the artifact. The algorithm converges even in the presence of severe noise.     

Use of an electromagnetic eye movement monitor for easy measurement of arm movements

This paper proposes a new technique for measuring arm movements, which is an adaptation of the electromagnetic method for measuring eye movements. Two small coils of wire are mounted onto the subject's elbow, moving rigidly with the humerus, and two more coils are mounted onto the subject's wrist, moving rigidly with the radius-ulna. The subject is placed inside three alternating magnetic fields at different frequencies in the X, Y, and Z directions. As the arm moves, the voltages induced into the coils vary with angle. For each coil, the voltages are de-modulated to give three dc voltages giving the vector direction of that coil's axis. Corrections for the nonuniformity of the magnetic fields are computed. The method works unambiguously for all possible arm movements within the physiological ranges of the joints. Measurement of finger angles is just as easily done. The five angles describing arm movements can be measured at millisecond intervals with noise as small as 2 arcsec rms and drift of about 1 arcmin over a day, i.e., the electronics is more stable than the attachment of the coils to the arm.     

An eye movement communication-control system for the disabled

The discrete electro-oculographic control system (DECS) has been developed as a communication tool for persons with severe handicaps. The system can be used as a means of adaptive control allowing persons with handicaps, especially those with only eye motor coordination to live more independent lives. This paper provides initial information about the design and capability of the DECS.     

眼睛运动模型的设计

现阶段,生物模式识别系统主要有两种实现方案,且这些方案的实现都与眼睛的运动有关,因此这里利用细胞神经网络（CNN）,基于欧氏距离的质心（COG）搜索算法以及距离权重选择模型（RSDW）的思想建立了一个眼睛运动模型。该模型输出的眼睛运动轨迹图特性与实际仪器测试的眼睛运动轨迹图特性具有较好的一致性,同时该模型能直接作为生物模式识别系统中信息获取模块的重要组成部分。     

人眼波前畸变的实时动态校正

以自适应光学技术为基础塔建了高分辨视网膜成像系统.利用微变形反射镜(DMs)作为波前校正器件,将镜面的形貌、波前及镜面的响应函数表示为泽尼克Zernike多项式的线性组合,利用直接迭代算法及控制电压矩阵改变镜面形貌,从而实现对眼睛波前畸变的适时校正.校正后残余误差的平方根值小于λ/7,接近衍射的极限分辨率.实验表明此闭环系统带宽小于5 Hz,能校正多数情况下眼睛的动态波前畸变,能对眼科医学的诊断提供一定的帮助.     

A method for accurate geometric correction of NOAA AVHRR HRPT data

A method for the geometric correction of NOAA Advanced Very High Resolution Radiometer (AVHRR) high-resolution picture transmission (HRPT) data is presented. After precise determination of nominal attitude angles for each time instant, geometric correction is done for ground control points (GCPs), and residual errors are interpreted as attitude angle variation effects and in this way corrected. All attitude angle deviations (in pitch, roll, and yaw) are simultaneously corrected by applying to two reference vectors (the vector normal to the scanning plane and the vector that defines the instantaneous viewing direction of the first pixel of each line) a three-axis rotation. A separate program performs the geometric correction, applying the orbital model to each point of the desired output geographical area. An application of this method is presented, in which AVHRR data are registered over a 1:25000 topographic map with subpixel accuracy, allowing the use of AVHRR data in a nearly local scale in combination with other high-resolution data, such as Landsat TM or SPOT     

基于低成本眼动记录系统的视线估计研究

高精度眼动记录技术现已非常成熟,但昂贵的价 格限制了当前商用眼动仪的应用 范围,发展灵 活、低成本的眼动记录系统将是眼动跟踪技术的重要研究方向。本文设计了一种 低成本、低侵 入性的耳麦式眼动记录系统。系统由两个普通CMOS摄像机及耳麦式支架构成,两个摄像机 分别记录注 视场景图像及人眼图像,成本仅为当前商用眼动仪的几百分之一。针对系统 采集的数据,提出一种分段 加权环形Hough变换算法提取虹膜轮廓及中心作为特征,采用支持向量回归(SVR)算法 估计注视点与特征点位置 的映射关系。设计了一种简便的标记注视点坐标的方法,实现注视估计。实验结果表明, 对场景图像中随机位置的注视方向估计平均误差为1.57°,表明低成本眼动仪可以满足日常 交互需求。     

An improved method for MRI artifact correction due to translational motion in the imaging plane

A computer postprocessing technique is developed to remove MRI artifact arising from unknown translational motion in the imaging plane. Based on previous artifact correction methods, the improved technique uses two successive steps to reduce read out and phase-encoding direction artifacts: First, the spectrum shift method is applied to remove read-out axis translational motion. Then, the phase retrieval method is employed to eliminate the remaining subpixel motion of the read-out axis and the entire motion of the phase-encoding axis. In the presence of noise, to protect edge detection (in the spectrum shift method), two high-density gray-level markers are added, one to each side of the imaging object. Experimental results with an actual MR scan confirmed the ability of the method to correct the artifact of an MR image caused by unknown translational motion in the imaging plane     

Robust, stable, and accurate boundary movement for physical etchingand deposition simulation

The increasing complexity of VLSI device interconnect features and fabrication technologies encountered by semiconductor etching and deposition simulation necessitates improvements in the robustness, numerical stability, and physical accuracy of the boundary movement method. The volume-mesh-based level set method, integrated with the physical models in SPEEDIE, demonstrates accuracy and robustness for simulations on a wide range of etching/deposition processes. The surface profile is reconstructed from the well-behaved level set function without rule-based algorithms. Adaptive gridding is used to accelerate the computation. The algorithm can be easily extended from two-dimensional (2-D) to three-dimensional (3-D), and applied to model microstructures consisting of multiple materials. Efficiency benchmarks show that this boundary movement method is practical in 2-D, and competitive for larger scale or 3-D modeling applications     

The linear homeomorphic saccadic eye movement model--a modification

The objective of this study was the modification of a linear homeomorphic horizontal saccadic eye movement model to a direct programming state-space representation through Laplace variable analysis about the operating point or initial eye position. The lateral and medial rectus muscle of each eye is modeled as a parallel combination of an active state tension generator with a viscosity and elastic element, connected to a series elastic element. The eyeball is modeled as a sphere connected to a viscosity and elastic element. Each of these elements is assumed to be ideal and linear.     

Computer correction of a microwave network analyzer without accurate frequency measurement

A method of calibration is described that uses three devices at a common reference plane, eliminating the requirement for accurate frequency measurement. The theoretical approach is supplemented with practical results and a discussion of the sources of error.     

Numerical study on the properties of an active sun tracker for solar streetlight

In this work, a new active sun tracker for solar streetlight combined with photoelectric tracking mode mainly and time-based tracking mode auxiliary was proposed. The sun tracker was designed through three aspects: mechanical structure, electrical system and control procedure. Then, a proper model named Available Energy Absorption Model was built to study the energy efficiency. The numerical average value of energy efficiency in a year is 36% which shows the superiority of the tracking mode on the available energy absorption. Lastly, the mechanical properties analysis of the tracker was implemented on two aspects which include motion simulation and wind resistance. The numerical results prove the feasibility of the double-slider mechanism and the reliability of the tracker’s strength.