不同空间频率通道的深度知觉及其质地的影响

我们设计了四种不同质地的随机点立体图对(RDS),并按照Wilson的空间频率通道的频带,分别利用Butterworth滤波器及Gabor函数对之进行了数字滤波处理,然后进行各种左右眼配对观察.得结果如下:1、Gabor函数滤波后图对的匹配结果好于Butterworth滤波器滤波后的图对.2、滤波后图对的匹配效果与图象质地有关.3、不同滤波的图对匹配大多也能形成立体感.4、在体视不同通道图对的匹配中,右眼对图象的高频成分更为敏感.     

一种滤除医学影像噪声的混合滤波算法

目的:医学影像在获取、存储、传输过程中会不同程度地受到噪声污染,这极大影像了其在临床诊疗中的应用。为了有效地滤除医学影像噪声,提出了一种混合滤波算法。方法:该算法首先将含有高斯和椒盐噪声的图像进行形态学开运算,然后对开运算后的图像进行二维小波分解,得到高频和低频小波分解系数。保留低频系数不变,将高频系数经过维纳滤波器进行滤波,最后进行小波系数重构。结果:采用该混合滤波算法、小波阈值去噪、中值滤波、维纳滤波分别对含有混合噪声的医学影像分别进行滤除噪声处理,该滤波算法去噪后影像的PSNR值明显高于其他三种方法。结论:该混合滤波算法是一种较为有效的医学影像噪声滤除方法。     

一种滤除医学影像噪声的混合滤波算法

目的：医学影像在获取、存储、传输过程中会不同程度地受到噪声污染,这极大影像了其在临床诊疗中的应用。为了有效地滤除医学影像噪声,提出了一种混合滤波算法。方法：该算法首先将含有高斯和椒盐噪声的图像进行形态学开运算,然后对开运算后的图像进行二维小波分解,得到高频和低频小波分解系数。保留低频系数不变,将高频系数经过维纳滤波器进行滤波,最后进行小波系数重构。结果：采用该混合滤波算法、小波阚值去噪、中值滤波、维纳滤波分别对含有混合噪声的医学影像分别进行滤除噪声处理,该滤波算法去噪后影像的PSNR值明显高于其他三种方法。结论：该混合滤波算法是一种较为有效的医学影像噪声滤除方法。     

高频超声联合低频超声检查诊断新生儿颅脑病变的临床价值研究

摘要 目的：探讨高频联合低频超声对新生儿颅脑病变的诊断价值,为新生儿颅脑病变的诊断提供依据。方法：选择2019年1月-2021年4月安徽省儿童医院接诊并疑似出现颅脑病变的新生儿62例作为研究对象,所有研究对象均应用高频超声联合低频超声探头对颅脑进行检查,并住院治疗。比较高频超声、低频超声、高频联合低频超声对新生儿颅脑病变的检出率;根据出院诊断结果比较高频超声、低频超声及联合检查与临床诊断符合情况及对颅脑病变的诊断价值。结果：高频超声检出颅脑病变35例（56.45%）,低频超声检出颅脑病变27例（43.55%）,高频超声联合低频超声检出颅脑病变53例（85.48%）,高频超声联合低频超声对新生儿颅脑病变的检出率显著高于高频超声、低频超声（P<0.05）;高频超声对新生儿颅脑病变的检出率显著高于低频超声（P<0.05）。高频联合低频超声对新生儿颅脑疾病诊断与临床诊断总体符合率高于高频超声、低频超声,高频超声对新生儿颅脑疾病诊断与临床诊断总体符合率高于低频超声（P<0.05）。高频联合低频超声对新生儿不同颅脑疾病诊断灵敏度、准确度显著高于高频超声、低频超声（P<0.05）,高频超声对新生儿不同颅脑疾病诊断灵敏度、准确度显著高于低频超声（P<0.05）,三种检查方法对新生儿不同颅脑疾病诊断特异度比较无统计学意义（P>0.05）。结论：高频联合低频超声检查诊断新生儿不同颅脑病变的灵敏度、准确度均较高,具有一定的临床应用价值。     

体视感觉“崩溃”的阀值

视差是产生体视感觉的主要因素.但视差过大时这种体视感觉也不能存在.这时随着双眼视差的增大从融合为单一像到成复像,而引起体视“崩溃”.本文对正常人和体视欠缺者用心理物理试验方法结合视觉诱发电位(VEP)分析,测量了人眼体视“崩溃”的视差上限阈值.并在改变刺激图形亮度和面积时加以比较.我们的结果表明正常人体视上限阈值,其视差高于2度,在某些情况下这个“崩溃”阈值达到3度.体视欠缺者的“崩溃”阈值约为1.5度.亮度和面积变小会使体视“崩溃”阈值下降,但在这种情况下体视欠缺者的“崩溃”阈值不会下降.可以认为1.5度是人的最低上限阈值·体视存在时VEP的N峰潜伏期约为220—300ms,P_3峰在280—340ms之间.无体视现象(视差为零和过大)这两个峰的潜伏期明显加大.     

人的体视超视锐度阈值

体视超视(?)象是视觉系统中(?)度的超(?)在一些特殊的(?)图形下,它的阈值可达2秒以下.考虑到人眼的一般体(?)锐度的60(?),(?)未超视度现象就是一个很有意义并值得注意研究的问题.对于如此精细的分辨能力,视(?)膜细胞可以说是很粗糙的(其直径约24秒)我们想了解,这么粗糙的视网膜是如何分辨出仅为其直径1/10的目标位差的呢?本文对人眼体视超视锐度现象做了一此研究,测定出体视超视锐度(?)值,并研究了低通滤波后对其影响.     

对刺激朝向改变的自动加工:事件相关电位的证据

利用事件相关电位（ＥＲＰ）技术,探讨非注意状态的刺激朝向改变是否引起自动加工。刺激为具有一定朝向（垂直和水平各５０％）和一定空间频率（低频９０％,高频１０％）的光栅。要求被试忽略光栅朝向,对高频光栅作反应。刺激呈现时间为５０ｍｓ,刺激间隔在２５０至４５０ｍｓ之间随机变化。低频光栅刺激被分为两类,“匹配”（与前一刺激朝向相同）和“失匹配”（与前一刺激朝向不同）。结果发现,失匹配刺激比匹配刺激诱发出更大的枕区Ｐ１、更大的前额－中央区Ｎ１以及更大的前部与顶区Ｐ２,但前部与顶区的Ｎ２却更小。这些ＥＲＰｓ变化提示,视觉对非注意的刺激朝向变化进行了一定程度的自动加工;视觉通道可能存在类似听觉失匹配负波（ＭＭＮ）的、然而机制不同的自动加工成分     

交替呈现随机点立体图对的时间特性

利用微机化的伪随机点立体图对发生器进行双眼体视的心理物理实验,研究交替呈现的随机点体图对(RDS)在达到双眼融合形成立体感知时信息输入的时间特性.实验结果表明,当RDS的交变频率达到4.8Hz以上时就能达到双眼的信息融合产生立体感知,但当交变频率低于62.5Hz时有图形的闪烁感.当交变频率等于62.5Hz时则产生稳定而清晰的立体感知.一幅RDS图对中的L(左)和R(右)图的呈现时间及其之间的交变时间的长短均对双眼的融合和立体感的形成有影响.L和R图的呈现时间和交变时间还存在一定的关系,以立体感形成为条件,如增大一定值的L和R图的呈现时间,则它们之间的交变时间必须相应减小,反之亦然.实验结果提示,双眼立体感知的形成不涉及单眼图象的长时记忆和短时记忆,仅有瞬时的视觉存储.     

不同氮素添加频率模拟氮沉降对桤木人工林生态系统碳储量的影响

为探究不同频率氮素添加模拟大气氮沉降对桤木人工林生态系统碳储量的影响, 采用野外固定样地观测的方法, 研究1年12次氮素添加(高频率)和1年2次氮素添加(低频率), 对桤木人工林生态系统乔木层、林下植被层、凋落物层、土壤层生物量及碳储量的影响。经过3年不同氮沉降模拟实验, 结果表明: (1) 高频与低频施氮均能增加桤木叶、枝、皮、根、总生物量及碳储量, 其中高频施氮显著增加根生物量及碳储量, 较对照增加了22.98%、24.05%; 而低频施氮显著增加叶、干生物量及枝、叶碳储量。(2) 低频与高频施氮均显著降低了桤木林下植被生物量及碳储量, 较对照分别降低67.95%、83.97%和79.73%、70.27%, 对碳含量影响不显著。(3)高频与低频施氮均显著增加L层(0—20 cm)凋落物生物量及L层和F层(20—40 cm)凋落物碳储量, 且高频施氮>低频施氮; 低频施氮显著降低20—40 cm土壤碳储量, 较对照降低20.83%, 高频施氮则对土壤碳含量和土壤碳储量无显著影响。高频施氮显著增加桤木林人工生态系统中凋落物层碳储量, 显著降低林下植被层碳储量, 生态系统总碳储量增加; 低频施氮显著降低乔木层、林下植被层和凋落物层碳储量, 导致桤木林生态系统碳储量降低, 但两种处理影响均不显著。     

基于DSP与FPAA的电化学信号滤波器

目的：研究对自主研发的DNA电化学分析仪所采集电化学信号的噪声的滤除方法。方法：根据电化学噪声信号的特征及其频率分布范围,采用由现场可编程模拟阵列（FPAA）实现的有高阶低通滤波器和基于DSP实现的FIR数字滤波器相结合的方式,对混合在电化学信号中的高频噪声信号进行滤除。结果：对滤波结果进行分析,频率在100HZ以上的噪声信号基本滤除。结论：FPAA与DSP芯片的结合构成了一个稳定性高,线性相位特性好,实时性强的高效滤波器。     

The aesthetic experience of 'contour binding'

To find the diagnostic spatial frequency information in different painting styles (cubism, impressionism and realism), we have compared sensitivity (d') in distinguishing signal (subject of the painting) from noise with normal, high-pass and low-pass filtered images at long (150 ms) and short (30 ms) exposure. We found that for cubist-style images, d' increases with high-pass filtering compared with normal and low-pass filtered images, but decreases with low-pass filtering compared with normal images. These results indicate that channels with high spatial resolution provide the diagnostic information to solve the binding problem. Sensitivity for images in impressionist style was instead reduced by both low- and high-pass filtering. This indicates that both high and low spatial frequency channels play a role in solving the binding problem, suggesting the involvement of large collator units that group the response of small channels tuned to the same orientation. The difference between realism, which shows higher sensitivity for low-frequency filtering at short durations and cubism in which the binding problem is solved by high spatial frequency channels, has a corresponding difference in aesthetic judgment: the probability of judging a painting as 'intriguing' is larger with low-pass filtering than with high-pass filtering in realism, while the opposite is true for cubism. This suggests that the aesthetic experience is available during early processing of an image, and could preferentially influence high-level categorization of the subject of a painting.     

Study of parvocellular and magnocellular visual channels in normal subjects and in patients with psychopathology

We measured susceptibility to the Müller-Lyer illusion in schizophrenic patients and normal observers. The images of the Müller-Lyer figure were digitally filtered in a high-frequency and low-frequency band by wavelet filter. Patients with schizophrenia are more susceptible to Müller-Lyer illusion, than mentally healthy examinees. The images of the Müller-Lyer figure with low spatial frequency were perceived in a similar way by the schizophrenic patients on the initial stage of disease and the control subjects. Patients with schizophrenia were more sensitive to the Müller-Lyer illusion when the image contained only high or medium spatial frequency. Schizophrenic patients in advanced stage were more susceptible to the illusion while presented with all types of images of the Müller-Lyer figure than the control group. It is hypothesized that those differences arise from the mismatch work of the magnocellular and parvocellular systems. It is known that images with the high spatial frequencies are most relevant for the parvocellular visual channels. The magnocellular visual channels are most sensitive to the images with the low spatial frequencies. Thus these findings demonstrate a significant impairment in parvocellular pathway function in patients on initial stage of schizophrenia. The patients on advanced stage of schizophrenia demonstrate impairment of both the parvocellular and magnocellular systems.     

Directional features for automatic tumor classification of mammogram images

One way for breast cancer diagnosis is provided by taking radiographic (X-ray) images (termed mammograms) for suspect patients, images further used by physicians to identify potential abnormal areas thorough visual inspection. When digital mammograms are available, computer-aided based diagnostic may help the physician in having a more accurate decision. This implies automatic abnormal areas detection using segmentation, followed by tumor classification. This work aims at describing an approach to deal with the classification of digital mammograms. Patches around tumors are manually extracted to segment the abnormal areas from the remaining of the image, considered as background. The mammogram images are filtered using Gabor wavelets and directional features are extracted at different orientation and frequencies. Principal Component Analysis is employed to reduce the dimension of filtered and unfiltered high-dimensional data. Proximal Support Vector Machines are used to final classify the data. Superior mammogram image classification performance is attained when Gabor features are extracted instead of using original mammogram images. The robustness of Gabor features for digital mammogram images distorted by Poisson noise with different intensity levels is also addressed.     

Stereo disparity computation using Gabor filters

A solution to the correspondence problem for stereopsis is proposed using the differences in the complex phase of local spatial frequency components. One-dimensional spatial Gabor filters (Gabor 1946; Marcelja 1980), at different positions and spatial frequencies are convolved with each member of a stereo pair. The difference between the complex phase at corresponding points in the two images is used to find the stereo disparity. Disparity values are combined across spatial frequencies for each image location. Three-dimensional depth maps have been computed from real images under standard lighting conditions, as well as from random-dot stereograms (Julesz 1971). The algorithm can discriminate disparities significantly smaller than the width of a pixel. It is possible that a similar mechanism might be used in the human visual system.     

A Bayesian model of stereopsis depth and motion direction discrimination

 The extraction of stereoscopic depth from retinal disparity, and motion direction from two-frame kinematograms, requires the solution of a correspondence problem. In previous psychophysical work [Read and Eagle (2000) Vision Res 40: 3345–3358], we compared the performance of the human stereopsis and motion systems with correlated and anti-correlated stimuli. We found that, although the two systems performed similarly for narrow-band stimuli, broad-band anti-correlated kinematograms produced a strong perception of reversed motion, whereas the stereograms appeared merely rivalrous. I now model these psychophysical data with a computational model of the correspondence problem based on the known properties of visual cortical cells. Noisy retinal images are filtered through a set of Fourier channels tuned to different spatial frequencies and orientations. Within each channel, a Bayesian analysis incorporating a prior preference for small disparities is used to assess the probability of each possible match. Finally, information from the different channels is combined to arrive at a judgement of stimulus disparity. Each model system – stereopsis and motion – has two free parameters: the amount of noise they are subject to, and the strength of their preference for small disparities. By adjusting these parameters independently for each system, qualitative matches are produced to psychophysical data, for both correlated and anti-correlated stimuli, across a range of spatial frequency and orientation bandwidths. The motion model is found to require much higher noise levels and a weaker preference for small disparities. This makes the motion model more tolerant of poor-quality reverse-direction false matches encountered with anti-correlated stimuli, matching the strong perception of reversed motion that humans experience with these stimuli. In contrast, the lower noise level and tighter prior preference used with the stereopsis model means that it performs close to chance with anti-correlated stimuli, in accordance with human psychophysics. Thus, the key features of the experimental data can be reproduced assuming that the motion system experiences more effective noise than the stereoscopy system and imposes a less stringent preference for small disparities. Received: 2 March 2001 / Accepted in revised form: 5 July 2001     

A Local Agreement Filtering Algorithm for Transmission EM Reconstructions

We present LAFTER, an algorithm for de-noising single particle reconstructions from cryo-EM.Single particle analysis entails the reconstruction of high-resolution volumes from tens of thousands of particle images with low individual signal-to-noise. Imperfections in this process result in substantial variations in the local signal-to-noise ratio within the resulting reconstruction, complicating the interpretation of molecular structure. An effective local de-noising filter could therefore improve interpretability and maximise the amount of useful information obtained from cryo-EM maps.LAFTER is a local de-noising algorithm based on a pair of serial real-space filters. It compares independent half-set reconstructions to identify and retain shared features that have power greater than the noise. It is capable of recovering features across a wide range of signal-to-noise ratios, and we demonstrate recovery of the strongest features at Fourier shell correlation (FSC) values as low as 0.144 over a 256³-voxel cube. A fast and computationally efficient implementation of LAFTER is freely available.We also propose a new way to evaluate the effectiveness of real-space filters for noise suppression, based on the correspondence between two FSC curves: 1) the FSC between the filtered and unfiltered volumes, and 2) C_ref, the FSC between the unfiltered volume and a hypothetical noiseless volume, which can readily be estimated from the FSC between two half-set reconstructions.     

Preventing errors when estimating single channel properties from the analysis of current fluctuations.

The conductance, number, and mean open time of ion channels can be estimated from fluctuations in membrane current. To examine potential errors associated with fluctuation analysis, we simulated ensemble currents and estimated single channel properties. The number (N) and amplitude (i) of the underlying single channels were estimated using nonstationary fluctuation analysis, while mean open time was estimated using covariance and spectral analysis. Both excessive filtering and the analysis of segments of current that were too brief led to underestimates of i and overestimates of N. Setting the low-pass cut-off frequency of the filter to greater than five times the inverse of the effective mean channel open time (burst duration) and analyzing segments of current that were at least 80 times the effective mean channel open time reduced the errors to < 2%. With excessive filtering, Butterworth filtering gave up to 10% less error in estimating i and N than Bessel filtering. Estimates of mean open time obtained from the time constant of decay of the covariance, tau obs, at low open probabilities (Po) were much less sensitive to filtering than estimates of i and N. Extrapolating plots of tau obs versus mean current to the ordinate provided a method to estimate mean open time from data obtained at higher Po, where tau obs no longer represents mean open time. Bessel filtering gave the least error when estimating tau obs from the decay of the covariance function, and Butterworth filtering gave the least error when estimating tau obs from spectral density functions.     

Stereopsis measured by random-dot patterns--a new clinical test.

Comparative measures are presented of stereo-acuity by random-dot stereograms using a phase difference haploscope and a Titmus stereogram. Using two groups of fifteen subjects each, one with full binocular vision and the other of small-angle strabismic amblyopes, greater discrimination between subject groups was found with the random-dot stereograms. It is concluded that random-dot stereograms produced by crossed Polaroid would be a more effective clinical means of determining stereo-acuity.     

Spike latency and jitter of neuronal membrane patches with stochastic Hodgkin-Huxley channels

Ion channel stochasticity can influence the voltage dynamics of neuronal membrane, with stronger effects for smaller patches of membrane because of the correspondingly smaller number of channels. We examine this question with respect to first spike statistics in response to a periodic input of membrane patches including stochastic Hodgkin-Huxley channels, comparing these responses to spontaneous firing. Without noise, firing threshold of the model depends on frequency—a sinusoidal stimulus is subthreshold for low and high frequencies and suprathreshold for intermediate frequencies. When channel noise is added, a stimulus in the lower range of subthreshold frequencies can influence spike output, while high subthreshold frequencies remain subthreshold. Both input frequency and channel noise strength influence spike timing. Specifically, spike latency and jitter have distinct minima as a function of input frequency, showing a resonance like behavior. With either no input, or low frequency subthreshold input, or input in the low or high suprathreshold frequency range, channel noise reduces latency and jitter, with the strongest impact for the lowest input frequencies. In contrast, for an intermediate range of suprathreshold frequencies, where an optimal input gives a minimum latency, the noise effect reverses, and spike latency and jitter increase with channel noise. Thus, a resonant minimum of the spike response as a function of frequency becomes more pronounced with less noise. Spike latency and jitter also depend on the initial phase of the input, resulting in minimal latencies at an optimal phase, and depend on the membrane time constant, with a longer time constant broadening frequency tuning for minimal latency and jitter. Taken together, these results suggest how stochasticity of ion channels may influence spike timing and thus coding for neurons with functionally localized concentrations of channels, such as in “hot spots” of dendrites, spines or axons.