A hybrid image processing system for X-ray images of an external fixator

In the field of orthopaedics, treatment of extremity deformities can be realised by means of external fixators. However, control of such biomedical system is very difficult. Some different mathematical models have been developed to improve quality of this service. Most of the parameters, which are used in these models, have been obtained from two orthogonal X-ray images: one from anteroposterior, AP, direction and the other from a lateral, L, direction. The quality of the results of this model is dependent on the accuracy of the input parameters. Measuring these parameters is a time-consuming issue, and the accuracy of the results is also low. To increase the quality of the measurement, the reference points should be chosen from the edges of the biomedical system, and it is important to find the edges without noise. To achieve this purpose, Sobel edge detector, binary large object analysis, thresholding and inverting are applied as image processing steps. The results are compared with manual measurement values which have been obtained earlier. The results show that semi-automatic measurement of the parameters is more accurate and faster than manual measurement. It shows that the efficiency of the fixator method has been improved.     

A hybrid image processing system for X-ray images of an external fixator

In the field of orthopaedics, treatment of extremity deformities can be realised by means of external fixators. However, control of such biomedical system is very difficult. Some different mathematical models have been developed to improve quality of this service. Most of the parameters, which are used in these models, have been obtained from two orthogonal X-ray images: one from anteroposterior, AP, direction and the other from a lateral, L, direction. The quality of the results of this model is dependent on the accuracy of the input parameters. Measuring these parameters is a time-consuming issue, and the accuracy of the results is also low. To increase the quality of the measurement, the reference points should be chosen from the edges of the biomedical system, and it is important to find the edges without noise. To achieve this purpose, Sobel edge detector, binary large object analysis, thresholding and inverting are applied as image processing steps. The results are compared with manual measurement values which have been obtained earlier. The results show that semi-automatic measurement of the parameters is more accurate and faster than manual measurement. It shows that the efficiency of the fixator method has been improved.     

Pré-traitement d’un volume IRM par filtrage anisotrope robuste pour la segmentation de l’épaule

A novel pre-treatment process for image segmentation, based on anisotropic diffusion and robust statistics, is presented in this paper. Image smoothing with edge preservation is shown to help upper limb segmentation (shoulder segmentation in particular) in MRI datasets. The anisotropic diffusion process is mainly controlled by an automated stopping function that depends on the values of voxel gradient. Voxel gradients are divided into two classes: one for high values, corresponding to edge voxels or noisy voxels, one for low values. The anisotropic diffusion process is also controlled by a threshold on voxel gradients that separates both classes. A global estimation of this threshold parameter is classically used. In this paper, we propose a new method based on a local robust estimation. It allows a better removing of noise while preserving edges in the images. An entropy criterion is used to quantify the ability of the algorithm to remove noise with different signal to noise ratios in synthetic images. Another quantitative evaluation criterion based on the Pratt Figure of Merit (FOM) is proposed to evaluate the edge preservation and their location accuracy with respect to a manual segmentation. The results on synthetic and MRI data of shoulder show the assets of the local model in terms of areas homogeneity and edges locations.     

基于多小波的胃癌病理细胞图像边缘检测与分析

对胃癌细胞图像的多尺度小波变换边缘检测进行了研究,为医生运用现代信息理论的方法进行相关疾病诊断提供了一种新的思路和途径。提出了多尺度小波边缘检测的新方法,归纳了改善小波边缘检测效果的一些策略。实验结果表明,对于具有复杂纹理的医学病理细胞图像,采用传统的边缘检测方法会产生伪边缘和方向性误差,它影响了图像边缘检测的可信度;而运用小波变换的时频尺度特性和对奇异变化的优良检测性能,可得到无噪声污染的图像实际边缘。     

西双版纳片断化热带雨林常绿乔木幼树水分利用效率的边缘效应研究

以植物叶片δ     

Reversibility of the effect of the change in time of the magnetic field on molluscan neurons

Influence of a single impulse of magnetic field (MF) of trapezoidal shape with 10 Oe amplitude on neuron electrical activity (EA) of Lymnaea stagnalis was studied. It has been found that both leading and trailing edges of MF impulse separately were able to change EA of the cells. Nevertheless the impulses with a short time between the edges were found to be of small efficiency. It was suggested that the influence of the rotation electric field induced by the leading edge of this pulse was abolished by the influence of that induced by the trailing edge. The efficiency of MF impulse influence increased with increasing the interval between their edges and ran to the maximum during 10 s interval.     

It’s noisy out there! A review of denoising techniques in cryo-electron tomography

Cryo-electron tomography is the only technique that can provide sub-nanometer resolved images of cell regions or even whole cells, without the need of labeling or staining methods. Technological advances over the past decade in electron microscope stability, cameras, stage precision and software have resulted in faster acquisition speeds and considerably improved resolution. In pursuit of even better image resolution, researchers seek to reduce noise – a crucial factor affecting the reliability of the tomogram interpretation and ultimately limiting the achieved resolution. Sub-tomogram averaging is the method of choice for reducing noise in repetitive objects. However, when averaging is not applicable, a trade-off between reducing noise and conserving genuine image details must be achieved. Thus, denoising is an important process that improves the interpretability of the tomogram not only directly but also by facilitating other downstream tasks, such as segmentation and 3D visualization. Here, I review contemporary denoising techniques for cryo-electron tomography by taking into account noise-specific properties of both reconstruction and detector noise. The outcomes of different techniques are compared, in order to help researchers select the most appropriate for each dataset and to achieve better and more reliable interpretation of the tomograms.     

Estimation of cell size from pulse shape in flow cytofluorometry.

The fluorescence pulse widths (pulse duration) generated by fluorochromed cells in a flow-through cytofluorometer provide useful information regarding cell (or nuclear) size and possibly other morphologic features. Simple fixed thresholds just above background noise can be used to identify these pulses, but measurements are then strongly affected by random noise and will vary as a result of both pulse amplitude and pulse shape. In this paper, we propose two alternative, amplitude-independent estimates of pulse width. The first is based on a threshold at some fraction of pulse height, or on a pair of thresholds scaled to some fixed central fraction of the total integrated intensity. The second is based on the ratio of pulse area to peak height. The quantitative properties of these width estimators is studied with simulated fluorescence pulses and with experimental specimens of fluorchromed polystyrene spheres, pollen and spores of known different diameters. The results indicated that absolute particle diameters can be measured within a precision of approximately 1 mu using instruments for flow cytofluorometry.     

Method for Assessing the Reliability of Molecular Diagnostics Based on Multiplexed SERS-Coded Nanoparticles

Surface-enhanced Raman scattering (SERS) nanoparticles have been engineered to generate unique fingerprint spectra and are potentially useful as bright contrast agents for molecular diagnostics. One promising strategy for biomedical diagnostics and imaging is to functionalize various particle types (“flavors”), each emitting a unique spectral signature, to target a large multiplexed panel of molecular biomarkers. While SERS particles emit narrow spectral features that allow them to be easily separable under ideal conditions, the presence of competing noise sources and background signals such as detector noise, laser background, and autofluorescence confounds the reliability of demultiplexing algorithms. Results obtained during time-constrained in vivo imaging experiments may not be reproducible or accurate. Therefore, our goal is to provide experimentalists with a metric that may be monitored to enforce a desired bound on accuracy within a user-defined confidence level. We have defined a spectral reliability index (SRI), based on the output of a direct classical least-squares (DCLS) demultiplexing routine, which provides a measure of the reliability of the computed nanoparticle concentrations and ratios. We present simulations and experiments to demonstrate the feasibility of this strategy, which can potentially be utilized for a range of instruments and biomedical applications involving multiplexed SERS nanoparticles.     

The response of a model neurone to a white noise input

We consider a simple model of a neurone in which the input voltage is integrated to form the somatic potential, and a pulse is emitted when this reaches a threshold; the somatic potential is then reset to its resting value. We subject this model to a white-noise input, and evaluate the cross correlation between input white noise and the output pulse train; this is proportional to the small-signal impulse response of the model. Some numerical estimations are presented.     

Traffic noise impacts on urban forest soundscapes in south‐eastern Australia

While the negative impacts of road infrastructure on faunal diversity and abundance have been extensively studied, many traffic noise studies have been conducted in the presence of confounding factors. Therefore, the extent to which traffic noise alone is responsible for impacts is not well known and a better understanding is required to inform urban planning and management decisions. We examined the impact of traffic noise on soundscape patterns at road edges in urban forests. Acoustic sensors were deployed at road and powerline edges, as well as within interior habitat, at three sites in south‐east Queensland, Australia. Powerline edges were included to separate edge effects from traffic noise impacts. We used soundscape power (normalized watts per kHz) of technophony (traffic noise in the 1–2 kHz range) and biophony (animal sounds in the 3–11 kHz range) to investigate soundscape patterns. The results showed that biophony was consistently lower at road edges and was negatively correlated with traffic noise and positively correlated with distance to road edge. Technophony was higher at road edges and was found to correlate negatively with distance to road edge and positively with traffic noise. Technophony and biophony at powerline edges generally exhibited values comparable to interior habitat. These results indicate that traffic noise affects urban forest soundscape patterns at road edges in south‐eastern Australia.     

Bilateral edge filter: photometrically weighted, discontinuity based edge detection

Edge-detection algorithms have the potential to play an increasingly important role both in single particle analysis (for the detection of randomly oriented particles), and in tomography (for the segmentation of 3D volumes). However, the majority of traditional linear filters are significantly affected by noise as well as artefacts, and offer limited selectivity. The Bilateral edge filter presented here is an adaptation of the Bilateral filter [Jiang, W., Baker, M.L., Wu, Q., Bajaj, C., Chiu, W., 2003. Applications of a bilateral denoising filter in biological electron microscopy. J. Struct. Biol. 144, 114-122] designed for enhanced edge detection. It uses photometric weighting to identify significant discontinuities (representing edges), minimizing artefacts and noise. Compared with common edge-detectors (LoG, Marr-Hildreth) the Bilateral edge filter yielded significantly better results. Indeed data was of a similar quality to that of the Canny edge-detector, which is considered as a leading standard in edge detection [Basu, M., 2002. Gaussian-based edge-detection methods-a survey. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 32, 252-260]. Compared to the Canny edge-detector the Bilateral edge-detector has the advantages that it only requires the adjustment of a single parameter, is theoretically faster for reasonably sized images, and can be used in selective contrast enhancement of images. The simplicity and speed of the filter for single particle and tomographic analysis are discussed.     

Frequency discrimination of brief tonal steps as a function of frequency in the lesser bulldog bat

In a two-alternative, forced-choice task lesser bulldog bats were trained to distinguish between a pure tone pulse and a pulse composed of a series of brief tonal steps oscillating between two different frequencies. The tone-step pulse gradually approximates the pure tone pulse as the frequency difference between the steps becomes progressively smaller. Frequency difference limens for the brief tonal frequency steps were determined for a broad range of ultrasonic frequencies. The variation in tone-step difference limens with frequency appears to be correlated to the frequency structure of the bat's short-constant-frequency/frequency-modulated echolocation sound. There was a marked decline in the value of the relative frequency difference limens (Weber ratio) over a fairly narrow range of frequencies above the constant frequency and a sharp increase in threshold above this range. The relative thresholds for frequency discrimination were small and uniform over the frequency range of the frequency-modulated sweep and increased for frequencies below the frequency- modulated sweep. Thus, the most accurate frequency-discrimination abilities occur over a narrow frequency range around the frequency of the constant-frequency component of returning echoes. Frequency discrimination over the range of frequencies of the frequency-modulated component is relatively good. Accepted: 20 March 1999     

Models of retinal signal processing at high luminances

Summary In psychophysics the relation between the threshold luminance increment and the background luminance for visual increment detection, is known to become linear for high luminances. This so called Weber-law means that at high luminances the threshold is caused by the detection apparatus, and not by the quantum noise of the stimulus itself. A simple machine implementing the Weber-law is discussed. This machine obviates the need for an internal noise source (or dark light). It is the combined result of an apparatus that reduces the output event rate by causing the quantum to spike ratio to follow the input intensity, and a detection criterion that needs a constant number of extra output events to generate a positive response. The dynamic properties of the machine are described by the solutions of a simple though nonlinear differential equation. The supra threshold properties prove to mimic several of the responses known to occur at ganglion cell level in the cat's retina. A tentative model of an on-center receptive field is presented, and results obtained by simulating this model on a digital cumputer are compared with some recent electrophysiological findings. Finally a possible extension of the model to a full on-center/off-surround receptive field model is discussed.The authors are indebted to the Netherlands Organisation for the Advancement of Pure Research (Z.W.O.) for financial support of a part of this investigation.We thank W. A. Aarnink for invaluable help in debugging and running the programs involved in this work.     

Effect of exposure duration,contrast and base blur on coding and discrimination of edges

We extend a neural network model, developed to examine neural correlates for the dynamic synthesis of edges from luminance gradients (O?men, 1993), to account for the effects of exposure duration, base blur and contrast on the perceived sharpness of edges. This model of REtino-COrtical Dynamics (RECOD) predicts that (i) a decrease in exposure duration causes an increase in the perceived blur and the blur discrimination threshold for edges, (ii) this increase in perceived blur is more pronounced for sharper edges than for blurred edges, (iii) perceived blur is independent of contrast while the blur discrimination threshold decreases with contrast, (iv) perceived blur increases with increasing base blur while the blur discrimination threshold has a nonmonotonic U-shaped dependence on base blur, (v) the perceived location of an edge shifts progressively towards the low-luminance side of the edge with increasing contrast, and (vi) perceived contrast of suprathreshold stimuli is essentially independent of spatial frequency over a wide range of contrast values. These predictions are shown to be in quantitative agreement with existing psychophysical data from the literature and with data collected on three observers to quantify the effect of exposure duration on perceived blur.     

Method for recording short latency evoked potentials using an EKG artifact elimination procedure

This paper describes the application of an EKG elimination procedure¹, previously reported by the authors, to evoked potentials (EPs) recording using a non-cephalic reference. The method consists of three separate steps: data acquisition, EKG artifact elimination, and EP averaging. EKG artifacts are eliminated from the raw EEG by applying a four step procedure to the simultaneously recorded EEG, EKG and stimulus pulse. The steps are: synchronized partition of the raw EEG, EKG averaging, synchronized repetition, and synchronized subtraction of the EKG estimate from the raw EEG. Average EP values are then obtained by averaging the processed EEG using the stimulus pulse as a trigger. Somatosensory evoked potentials to a hand reference, averaged using the proposed method, were compared with those obtained by two conventional averaging methods, and were shown to be more clearly defined. The advantage of the proposed method for recording short latency EP values with a non-cephalic reference is that it requires fewer sweeps and thus takes less time than other methods. The proposed method may also be applicable to the recording of other EP values.     

Texturerkennung und texturreproduktion

Computer generated textures are used to examine the recognition of pictorial textures and their edges by supervised learning. Since the recognition of texture at a given spot of the image involves measurements within a certain neighborhood of this spot, misclassification occurs at the edge between different textures, as was shown in Part 1. The edge enhancement procedures do also not produce a sharp edge. Based on some psychooptical evidence, a propagation operator is utilized to define the edges. First, the textures are classified only in those regions where a high level of confidence exists, the rest of the picture being marked as unrecognized. Second, the unrecognized picture elements adjoining a recognized spot are given its class, thus enlarging the recognized area. This process is repeated a few times, the limit being the propagation of results over an area greater than the neighborhood within which the texture parameters were measured in the first instance. The procedure yields welldefined edges at the proper locations.     

Patterns of invertebrate biodiversity across a natural edge

Abstract Most ecologists are comfortable with the notion of habitats as recognizable entities and also with situations where the junction between two adjacent habitats forms a discrete edge. Such edges form naturally because of sharp changes in important edaphic, geomorphological, climatic or chemical properties to which plants, in particular, respond. Less clear is the effect of such edges on assemblages of mobile organisms, especially invertebrates that operate at relatively small spatial scales. The objective of the present study was to sample invertebrate composition across a natural edge between a well‐developed riparian habitat on fluvial sands and a saltbush habitat developed on a stony gibber plain in a semi‐arid region of New South Wales, Australia. A total of 150 pitfall traps on five 1‐km‐long transects that straddled the edge produced more than 13 000 adult specimens from 21 ordinal invertebrate taxa. A total of 10 446 beetle, ant, wasp, fly and springtail specimens were further sorted into 426 morphospecies. Comparisons and estimates of trends in abundance and richness were made, along with computation of multivariate dissimilarity and permutation statistics, to determine if the land system edge was coincident with changes in invertebrate abundance and composition. These analyses were unable to detect disjunctions in diversity coincident with the edge. The data suggest that many taxa are either present consistently in both habitats or are mostly found in one habitat but ‘leak’ several hundred metres across into the other. Few taxa were unique to either habitat. The result is that assemblage composition for invertebrates changes gradually over distances of up to 400 m either side of the edge and that the distance to a recognizable change in composition is taxon dependent. Even sharp habitat edges, as defined by discrete changes in soils and plants, are not edges but broad transition zones for many invertebrate taxa. There are several implications of these results, especially for landscape ecology.     

Some properties of auditory neuron’s model trained by firing caused by tones modulated by low-frequency noise

In many sensory systems the formation of burst firing can be observed along a way from the periphery to the central nuclei. We investigate the putative transformation of spontaneous activity in the auditory pathway using a neuron model trained by real firing recorded in the auditory nuclei of the frog. The model has 200 separate inputs (neuronal spines). It is supposed that every spine is a coincidence detector. Its output (synaptic potential) sharply increases at emergence of the precisely certain interpulse interval in an input pulse sequence. If the total synaptic potentials excess a threshold, the model generates output spike, which changes weight of all spines according to the simplified Hebb principle. The model was trained by real firing caused in the auditory nuclei of the frog by tones modulated by low-frequency noise in the frequency ranges of 0–15 Hz, 0–50 Hz or 0–150 Hz. After that training the synaptic weights of every spine essentially changed. Thus, along with some increase of weights of spines tuned to boundary frequencies of modulating noise, the most characteristic change was the emphasizing weights of spines tuned to short interpulse intervals. As a result the spontaneous activity passed through the trained model became much more bursting. Efficiency of a signal transmission in model was higher when input spontaneous activity of real cells contains bursts of spikes. Results of modeling are discussed in connection with modern physiological data demonstrating the functional advantage of bursting.