Accurate, automatic determination of astigmatism and phase with Ctfplotter in IMOD.

Ctfplotter in the IMOD software package is a flexible program for determination of CTF parameters in tilt series images. It uses a novel approach to find astigmatism by measuring defocus in one-dimensional power spectra rotationally averaged over a series of restricted angular ranges. Comparisons with Ctffind, Gctf, and Warp show that Ctfplotter's estimated astigmatism is generally more reliable than that found by these programs that fit CTF parameters to two-dimensional power spectra, especially at higher tilt angles. In addition to that intrinsic advantage, Ctfplotter can reduce the variability in astigmatism estimates further by summing results over multiple tilt angles (typically 5), while still finding defocus for each individual image. Its fitting strategy also produces better phase estimates. The program now includes features for tuning the sampling of the power spectrum so that it is well-represented for analysis, and for determining an appropriate fitting range that can vary with tilt angle. It can thus be used automatically in a variety of situations, not just for fitting tilt series, and has been integrated into the SerialEM acquisition software for real-time determination of focus and astigmatism.

Beat phenomena of oscillating readouts.

PURPOSE: To demonstrate slowly varying, erroneous magnetic field gradients for oscillating readouts due to the mechanically resonant behavior of gradient systems. METHODS: Projections of a static phantom were acquired using a one-dimensional (1D) EPI sequence with varying EPI frequencies ranging from 1121 to 1580 Hz on clinical 3T systems (30 mT/m, 200 T/m/s). Phase due to static B0 inhomogeneities was eliminated by a complex division of two separate scans with different polarities of the EPI readout. The temporal evolution of phase was evaluated and related to the mechanical resonances of the gradient systems derived from the gradient modulation transfer function. Additionally, the impact of temporally varying mechanical resonance effects on EPI was evaluated using an echo-planar spectroscopic imaging sequence. RESULTS: A beat phenomenon resulting in a slowly varying phase was observed. Its temporal frequency was given by the difference between the EPI frequency and the mechanical resonance frequency of the activated gradient axis. The maximum erroneous, oscillating phase during phase encoding was ±0.5 rad for an EPI frequency of 1281 Hz. Echo-planar spectroscopic imaging images showed the resulting time-dependent stretching/compression of the FOV. CONCLUSION: Oscillating readouts such as those used in EPI can result in low-frequency, erroneous phase contributions, which are explained by the beat phenomenon. Therefore, EPI phase-correction approaches may need to include beat effects for accurate image reconstruction.

An improved method to measure transfer functions using MRI.

PURPOSE: A previously published method for MRI-based transfer function assessment makes use of the so-called transceive phase assumption (TPA). This limits its applicability to shorter leads and/or lower field strengths. A new method is presented where the background electric field is determined from both B 1 + $$ {\mathrm{B}}_1^{+} $$ - and B 1 - $$ {\mathrm{B}}_1^{-} $$ -field distributions, avoiding the TPA and making it more generally applicable. THEORY AND METHODS: These B 1 $$ {\mathrm{B}}_1 $$ -distributions are determined from a spoiled gradient echo multiflip angle acquisition. From the separated B 1 $$ {\mathrm{B}}_1 $$ -components the background electrical field and the induced current are computed. Further improvement is achieved by recasting the B 1 $$ {\mathrm{B}}_1 $$ -field model as a "magnitude squared least squares" problem. The proposed reconstruction method is used to determine transfer functions of various copper wire lengths up to 40 cm inside an elliptical ASTM phantom. The method is first tested on EM-simulated data and subsequently phantom and bench measurements are used to determine transfer functions experimentally. RESULTS: In silica reconstructions demonstrate the validity of the proposed B 1 $$ {\mathrm{B}}_1 $$ -field model resulting in highly accurate reconstructed B 1 $$ {\mathrm{B}}_1 $$ -fields, currents, incident electric fields and transfer functions. The experimental results show slight deviations in the field model, however, resulting transfer functions are accurately determined with high similarity to simulations and comparable to bench measurements. CONCLUSION: A more generally applicable method for MRI-based transfer function assessment is presented. The proposed method circumvents phase assumptions making it applicable for longer objects and/or higher field strengths. Additional improvements are implemented in the B 1 $$ {\mathrm{B}}_1 $$ -mapping method and the solution algorithm.

Short-term dynamic characteristics of diuresis during exogenous pressure perturbations with and without arterial baroreflex control.

Although body fluid volume control by the kidneys may be classified as a long-term arterial pressure (AP) control system, it does not necessarily follow that the urine flow (UF) response to changes in AP is slow. We quantified the dynamic characteristics of the UF response to short-term AP changes by changing mean AP between 60 mmHg and 100 mmHg every 10 s according to a binary white noise sequence in anesthetized rats (n = 8 animals). In a baro-on trial (the carotid sinus baroreflex was enabled), the UF response represented the combined synergistic effects of pressure diuresis (PD) and neurally mediated antidiuresis (NMA). In a baro-fix trial (the carotid sinus pressure was fixed at 100 mmHg), the UF response mainly reflected the effect of PD. The UF step response was quantified using the sum of two exponential decay functions. The fast and slow components had time constants of 6.5 ± 3.6 s and 102 ± 85 s (means ± SD), respectively, in the baro-on trial. Although the gain of the fast component did not differ between the two trials (0.49 ± 0.21 vs. 0.66 ± 0.22 µL·min-1·kg-1·mmHg-1), the gain of the slow component was greater in the baro-on than in the baro-fix trial (0.51 ± 0.14 vs. 0.09 ± 0.39 µL·min-1·kg-1·mmHg-1, P = 0.023). The magnitude of NMA relative to PD was calculated to be 32.2 ± 29.8%. In conclusion, NMA contributed to the slow component, and its magnitude was approximately one-third of that of the effect of PD.NEW & NOTEWORTHY We quantified short-term dynamic characteristics of the urine flow (UF) response to arterial pressure (AP) changes using white noise analysis. The UF step response approximated the sum of two exponential decay functions with time constants of ∼6.5 s and 102 s. The neurally mediated antidiuretic (NMA) effect contributed to the slow component of the UF step response, with the magnitude of approximately one-third of that of the pressure diuresis (PD) effect.

Diatom cell-size composition as a novel tool for quantitative estimates of the water table in peatlands.

Diatom cell-size composition is an indicator of aquatic environmental changes but has been rarely investigated, especially in semi-terrestrial peatlands. In this study, both taxonomic composition and cell-size composition of diatoms were analysed in 41 samples from two montane peatlands, northeastern China. Redundancy analyses revealed that diatom taxonomic composition was significantly related to the depth to the water table (DWT) and Ca2+, while cell-size composition was significantly associated with DWT and Si. DWT was the most important factor and its sole effect explained 26.2% and 17.9% of the total variance in taxonomic composition and cell-size composition, respectively. Accordingly, diatom-based water-table transfer functions were developed based on taxonomic composition and cell-size composition, respectively. The maximum-likelihood (ML) model based on diatom taxonomic composition had the best performance, with a correlation coefficient value (R2) of 0.78 and the root mean squared error of prediction (RMSEP) of 6.66 cm. The ML model based on cell-size composition had similar performance, with an R2 of 0.78 and the RMSEP of 6.87 cm, suggesting that diatom cell-size composition can be a new quantitative means to track past water-table changes. This method requires further appraisal with palaeoecological data but offers a new option that deserves exploration.

Modulation transfer function of implantable phakic intraocular contact lens (IPCL) for myopia and presbyopia.

PURPOSE: This study aimed to assess the optical quality of myopic and presbyopic IPCLs with different additional powers, and to investigate the effects of pupil size on the optical quality of these IPCLs using an in-vitro modulation transfer function (MTF) measurement system. METHODS: Linear scatter functions (LSFs) were recorded using the OPAL Vector system and an eye phantom consisting of wet cells filled with a balanced salt solution. A myopic IPCL or a presbyopic IPCL was placed in the posterior chamber of this model. The MTF was calculated from the LSF using the fast Fourier transform techniques. The effective apertures were set at 2.0 to 5.0 mm in 1.0 mm steps. RESULTS: The in-focus MTF values of the myopic IPCL and presbyopic IPCL with additional powers of + 2.0 and + 4.0 diopters at 100 cycles/mm for an effective aperture of 3.0 mm were 43%, 27%, and 24%, respectively. The in-focus MTF value of both myopic and presbyopic IPCLs was the highest when the effective aperture was set at 3.0 mm, and it gradually worsened when the effective aperture became larger than 3.0 mm at 20, 60, and 100 cycles/mm. CONCLUSIONS: Both myopic and presbyopic IPCLs provided excellent MTF values, but the additional power profile can deteriorate optical performance in presbyopic IPCL-implanted eyes, even with a low additional power. Pupil size can influence visual quality in IPCL-implanted eyes for both myopia and presbyopia.

Comparative visual outcomes of the first versus second eye following small-incision lenticule extraction (SMILE).

BACKGROUND: This study aimed to compare the visual outcomes of the first operated eyes with those of the second operated eyes following small-incision lenticule extraction (SMILE). METHODS: A total of 202 patients (404 eyes) underwent SMILE using the tear film mark centration method for myopia and myopic astigmatism correction. Baseline characteristics, objective optical quality, decentered displacement, induced corneal aberrations, and modulation transfer function (MTF) values were assessed. Linear regression analyzed the relationship between decentration and visual quality parameters, including corneal aberrations and MTF values. RESULTS: No significant difference was observed in objective visual quality, efficacy, and safety indexes between the two groups (all P > 0.05). The average decentered displacement for the first and second surgical eyes was 0.278 ± 0.17 mm and 0.315 ± 0.15 mm, respectively (P = 0.002). The horizontal coma in the first surgical eyes were notably lower than in the second (P = 0.000). MTF values at spatial frequencies of 5, 10, 15, and 20 cycles/degree (c/d) were higher in the first surgical eyes compared to the second (all P < 0.05). Linear regression indicated that high-order aberrations (HOAs), root mean square (RMS) coma, spherical aberration, horizontal coma, vertical coma, and eccentric displacement were all linearly correlated. Furthermore, MTF values exhibited a linear relationship with eccentric displacement across these spatial frequencies. CONCLUSIONS: There was no discernible difference in visual acuity, efficacy, or safety between the two operated eyes. Nonetheless, the first operated eyes exhibited reduced decentered displacement and demonstrated superior outcomes in terms of horizontal coma and MTF values compared to the second operated eyes following SMILE. The variations in visual quality parameters were linearly correlated with decentered displacement.

3U CubeSat-Based Hyperspectral Remote Sensing by Offner Imaging Hyperspectrometer with Radially-Fastened Primary Elements.

This paper presents findings from a spaceborne Earth observation experiment utilizing a novel, ultra-compact hyperspectral imaging camera aboard a 3U CubeSat. Leveraging the Offner optical scheme, the camera's hyperspectrometer captures hyperspectral images of terrestrial regions with a 200 m spatial resolution and 12 nanometer spectral resolution across a 400 to 1000 nanometer wavelength range, covering 150 channels in the visible and near-infrared spectrums. The hyperspectrometer is specifically designed for deployment on a 3U CubeSat nanosatellite platform, featuring a robust all-metal cylindrical body of the hyperspectrometer, and a coaxial arrangement of the optical elements ensures optimal compactness and vibration stability. The performance of the imaging hyperspectrometer was rigorously evaluated through numerical simulations prior to construction. Analysis of hyperspectral data acquired over a year-long orbital operation demonstrates the 3U CubeSat's ability to produce various vegetation indices, including the normalized difference vegetation index (NDVI). A comparative study with the European Space Agency's Sentinel-2 L2A data shows a strong agreement at critical points, confirming the 3U CubeSat's suitability for hyperspectral imaging in the visible and near-infrared spectrums. Notably, the ISOI 3U CubeSat can generate unique index images beyond the reach of Sentinel-2 L2A, underscoring its potential for advancing remote sensing applications.

Exploring the Feasibility of Estimating Intraocular Pressure Using Vibrational Response of the Eye: A Methodological Approach.

This study addresses the limitations of current tonometry techniques by exploring vibroacoustic properties for estimating intraocular pressure (IOP), a key diagnostic parameter for monitoring glaucoma-a significant risk factor for vision loss. Utilizing vivo porcine eyeballs, we investigated the relationship between IOP and the nonlinear vibration transfer function ratio (NVTFR). Through applying varying vibration levels and analyzing responses with transfer function analysis and univariate regression, we identified a strong negative correlation between NVTFR and IOP, evidenced by a Pearson correlation coefficient of -0.8111 and significant results from generalized linear model (GLM) regression (p-value < 0.001). These findings indicate the potential of NVTFR as a vital indicator of IOP changes. Our study highlights the feasibility of using vibroacoustic properties, specifically NVTFR, to measure IOP. While further refinement is necessary for in vivo application, this approach opens new possibilities for non-invasive and patient-friendly IOP monitoring, potentially enhancing ophthalmology diagnostic techniques and providing a foundation for future research and development in this critical area.

Best Practices for Measuring the Modulation Transfer Function of Video Endoscopes.

Endoscopes are crucial for assisting in surgery and disease diagnosis, including the early detection of cancer. The effective use of endoscopes relies on their optical performance, which can be characterized with a series of metrics such as resolution, vital for revealing anatomical details. The modulation transfer function (MTF) is a key metric for evaluating endoscope resolution. However, the 2020 version of the ISO 8600-5 standard, while introducing an endoscope MTF measurement method, lacks empirical validation and excludes opto-electronic video endoscopes, the largest family of endoscopes. Measuring the MTF of video endoscopes requires tailored standards that address their unique characteristics. This paper aims to expand the scope of ISO 8600-5:2020 to include video endoscopes, by optimizing the MTF test method and addressing parameters affecting measurement accuracy. We studied the effects of intensity and uniformity of image luminance, chart modulation compensation, linearity of image digital values, auto gain control, image enhancement, image compression and the region of interest dimensions on images of slanted-edge test charts, and thus the MTF based on these images. By analyzing these effects, we provided recommendations for setting and controlling these factors to obtain accurate MTF curves. Our goal is to enhance the standard's relevance and effectiveness for measuring the MTF of a broader range of endoscopic devices, with potential applications in the MTF measurement of other digital imaging devices.

Validating computer applications for calculating spatial resolution and noise property in CT using simulated images with known properties.

The purpose of this study was to evaluate, using simulated images with known property values, how accurately some computer applications for calculating modulation transfer function (MTF), task transfer function (TTF), or noise power spectrum (NPS) in computed tomography (CT) based on widely known techniques produce their results. Specifically, they were three applications applicable to the wire method for MTF calculation, two applications corresponding to the circular edge (CE) and linear edge (LE) methods for TTF, and one application using a two-dimensional Fourier transform for NPS, which are collectively integrated with the software 'CTmeasure' provided by the Japanese Society of CT Technology. Images for the calculation with radial symmetry were generated based on a roll-off type filter function. The accuracy of each application was evaluated by comparing the calculated property with the true one. The calculated MTFs for the wire method accurately matched the true ones with percentage errors of smaller than 1.0%. In contrast, the CE and LE methods presented relatively large errors of up to 50% at high frequencies, whereas the NPS's errors were up to 30%. A closer investigation revealed, however, that these errors were attributable not to the applications but to the insufficiencies in the measurement techniques commonly employed. By improving the measurement conditions to minimize the effects of the insufficiencies, the errors notably decreased, whichvalidated the calculation techniques in the applications we used.

Design of uncertain displacement controlled velocity control system for hydraulic actuator.

Displacement-controlled systems have high efficiency and are widely used in industry. Accurate control of the actuator motion in hydraulic systems is usually a necessity in industrial applications such as the motion of control surfaces in fixed-wing airplanes for flight control as well as the aircraft brake systems. To address this need, the current study was conducted with the goal of developing a high-fidelity model to achieve precise control. This work focused on modeling a hydrostatic transmission that is used for controlling a linear actuator velocity. The flow entering the actuator was changed using a variable displacement pump. The study included examining the stability and performance of the open-loop system. Additionally, the study involved the design of the proportional-integral-derivative PID and H∞ controllers, followed by the analysis of the stability and performance of the closed-loop system with both controllers. Furthermore, the multiplicative uncertainty is taken into account and the robustness of the system is verified using controllers PID and H∞. In the current study,Uncertain parameters such as actuator efficiency, pump speed, and viscous friction coefficient were considered and allowed for a ±5% deviation from their stated values. Taking uncertainty into account ensures that the system performs properly even in case where the design parameters vary within the specified range. The system response is compared for the cases of open-loop system, closed-loop system with PID controller, and closed-loop system with H∞ controller. The results demonstrated that the open-loop system remains stable for real-world applications but shows insufficient performance in terms of input tracking and disturbance rejection. The introduction of the PID controller significantly enhanced the system's response to a reference input; however, its disturbance rejection capabilities in terms of overshoot and settling time were still unsatisfactory. The system equipped with the PID controller failed to meet the robustness requirements. Conversely, the utilization of H∞ controllers yielded superior responses and fulfilled the robustness criteria.

Multiresolution directed transfer function approach for segment-wise seizure classification of epileptic EEG signal.

Currently, with the bloom in artificial intelligence (AI) algorithms, various human-centered smart systems can be utilized, especially in cognitive computing, for the detection of various chronic brain diseases such as epileptic seizure. The primary goal of this research article is to propose a novel human-centered cognitive computing (HCCC) method for segment-wise seizure classification by employing multiresolution extracted data with directed transfer function (DTF) features, termed as the multiresolution directed transfer function (MDTF) approach. Initially, the multiresolution information of the epileptic seizure signal is extracted using a multiresolution adaptive filtering (MRAF) method. These seizure details are passed to the DTF where the information flow of high frequency bands is computed. Thereafter, different measures of complexity such as approximate entropy (AEN) and sample entropy (SAEN) are computed from the extracted high frequency bands. Lastly, a k-nearest neighbor (k-NN) and support vector machine (SVM) are used for classifying the EEG signal into non-seizure and seizure data depending on the multiresolution based information flow characteristics. The MDTF approach is tested on a standard dataset and validated using a dataset from a local hospital. The proposed technique has obtained an average sensitivity of 98.31%, specificity of 96.13% and accuracy of 98.89% using SVM classifier. The average detection rate of the MDTF approach is 97.72% which is greater than the existing approaches. The proposed MDTF method will help neuro-specialists to locate seizure information drift which occurs within the consecutive segments and between two channels. The main advantage of the MDTF approach is its capability to locate the seizure activity contained by the EEG signal with accuracy. This will assist the neurologists with the precise localization of the epileptic seizure automatically and hence will reduce the burden of time-consuming epileptic seizure analysis.

Modeling the Electrical Activity of the Heart via Transfer Functions and Genetic Algorithms.

Although healthcare and medical technology have advanced significantly over the past few decades, heart disease continues to be a major cause of mortality globally. Electrocardiography (ECG) is one of the most widely used tools for the detection of heart diseases. This study presents a mathematical model based on transfer functions that allows for the exploration and optimization of heart dynamics in Laplace space using a genetic algorithm (GA). The transfer function parameters were fine-tuned using the GA, with clinical ECG records serving as reference signals. The proposed model, which is based on polynomials and delays, approximates a real ECG with a root-mean-square error of 4.7% and an R2 value of 0.72. The model achieves the periodic nature of an ECG signal by using a single periodic impulse input. Its simplicity makes it possible to adjust waveform parameters with a predetermined understanding of their effects, which can be used to generate both arrhythmic patterns and healthy signals. This is a notable advantage over other models that are burdened by a large number of differential equations and many parameters.

S-shaped grey wolf optimizer-based FOX algorithm for feature selection.

The FOX algorithm is a recently developed metaheuristic approach inspired by the behavior of foxes in their natural habitat. While the FOX algorithm exhibits commendable performance, its basic version, in complex problem scenarios, may become trapped in local optima, failing to identify the optimal solution due to its weak exploitation capabilities. This research addresses a high-dimensional feature selection problem. In feature selection, the most informative features are retained while discarding irrelevant ones. An enhanced version of the FOX algorithm is proposed, aiming to mitigate its drawbacks in feature selection. The improved approach referred to as S-shaped Grey Wolf Optimizer-based FOX (FOX-GWO), which focuses on augmenting the local search capabilities of the FOX algorithm via the integration of GWO. Additionally, the introduction of an S-shaped transfer function enables the population to explore both binary options throughout the search process. Through a series of experiments on 18 datasets with varying dimensions, FOX-GWO outperforms in 83.33 % of datasets for average accuracy, 61.11 % for reduced feature dimensionality, and 72.22 % for average fitness value across the 18 datasets. Meaning it efficiently explores high-dimensional spaces. These findings highlight its practical value and potential to advance feature selection in complex data analysis, enhancing model prediction accuracy.

A brain functional network feature extraction method based on directed transfer function and graph theory for MI-BCI decoding tasks.

Background: The development of Brain-Computer Interface (BCI) technology has brought tremendous potential to various fields. In recent years, prominent research has focused on enhancing the accuracy of BCI decoding algorithms by effectively utilizing meaningful features extracted from electroencephalographic (EEG) signals. Objective: This paper proposes a method for extracting brain functional network features based on directed transfer function (DTF) and graph theory. The method incorporates the extracted brain network features with common spatial pattern (CSP) to enhance the performance of motor imagery (MI) classification task. Methods: The signals from each electrode of the EEG, utilizing a total of 32 channels, are used as input signals for the network nodes. In this study, 26 healthy participants were recruited to provide EEG data. The brain functional network is constructed in Alpha and Beta bands using the DTF method. The node degree (ND), clustering coefficient (CC), and global efficiency (GE) of the brain functional network are obtained using graph theory. The DTF network features and graph theory are combined with the traditional signal processing method, the CSP algorithm. The redundant network features are filtered out using the Lasso method, and finally, the fused features are classified using a support vector machine (SVM), culminating in a novel approach we have termed CDGL. Results: For Beta frequency band, with 8 electrodes, the proposed CDGL method achieved an accuracy of 89.13%, a sensitivity of 90.15%, and a specificity of 88.10%, which are 14.10, 16.69, and 11.50% percentage higher than the traditional CSP method (75.03, 73.46, and 76.60%), respectively. Furthermore, the results obtained with 8 channels were superior to those with 4 channels (82.31, 83.35, and 81.74%), and the result for the Beta frequency band were better than those for the Alpha frequency band (87.42, 87.48, and 87.36%). Similar results were also obtained on two public datasets, where the CDGL algorithm's performance was found to be optimal. Conclusion: The feature fusion of DTF network and graph theory features enhanced CSP algorithm's performance in MI task classification. Increasing the number of channels allows for more EEG signal feature information, enhancing the model's sensitivity and discriminative ability toward specific activities in brain regions. It should be noted that the functional brain network features in the Beta band exhibit superior performance improvement for the algorithm compared to those in the Alpha band.

Bio inspired heuristic computing scheme for the human liver nonlinear model.

In this research, a bio-inspired heuristic computing approach has been developed to solve the nonlinear behavior of the human liver, which is categorized into the liver and blood. The solutions of the human liver model are presented by using the stochastic computation procedure based on the artificial neural network (ANN) along with the optimization of genetic algorithm (GA) and interior-point (IP). A fitness function is designed through the differential form of the nonlinear human liver model and then optimized by using the hybrid competency of GAIP scheme. The correctness and exactness of the proposed approach are observed through the overlapping of the obtained (GAIP) and reference (Adams scheme) solutions, while the calculated absolute error values in good order enhance the worth of the proposed solver. The log-sigmoid transfer function together with ten numbers of neurons is executed to perform the solutions of the human liver nonlinear model. Furthermore, the statistical approaches have been applied in order to observe the reliability of the designed approach for solving the nonlinear human liver model.

Modulation transfer function of digital breast tomosynthesis: a comparison of various edge devices.

The modulation transfer function (MTF) is a fundamental tool for assessing the sharpness of digital breast tomosynthesis (DBT) systems and is primarily measured using edge devices. We compared the MTF of a Senographe Pristina DBT system using four-edge devices. These devices were composed of stainless steel with a thickness of 0.6, 0.8, and 1.0 mm, and 1.0 mm tungsten, based on different international guidelines. We evaluated spatial frequencies at MTFs of 0.5 (MTF50%) and 0.1 (MTF10%). The collimator-equipped and non-collimator configurations of the DBT were compared. We found no appreciable differences between scan and chest wall-nipple directions. Both MTF50% (2.90-2.99 cycles/mm) and MTF10% (6.69-6.94 cycles/mm) demonstrated minimal variation across the different edge devices. The collimator-equipped system exhibited an MTF50% that was approximately 5% higher than that of the non-collimator configuration. The choice of the edge device did not appreciably impact the MTF.