Automatic Threshold Determination Research Articles

Comparison of Two Measurement Paradigms to Determine Electrically Evoked Cochlear Nerve Responses and Their Correlation to Cochlear Nerve Cross-section in Infants and Young Children With Cochlear Implant.

Electrically evoked compound action potentials (ECAPs) are used for intra-/postoperative monitoring with intracochlear stimulation of cochlear implants. ECAPs are recorded in MED-EL (Innsbruck, Austria) implants using auditory response telemetry (ART), which has been further developed with automatic threshold determination as AutoART. The success of an ECAP measurement also depends on the number of available spiral ganglion cells and the bipolar neurons of the cochlear nerve (CN). It is assumed that a higher population of spiral ganglion cell implies a larger CN cross-sectional area (CSA), which consequently affects ECAP measurements. Intraoperative ECAP measurements from 19 implanted ears of children aged 8 to 18 months were retrospectively evaluated. A comparison and correlation of ART/AutoART ECAP thresholds/slopes at electrodes E2 (apical), E6 (medial), E10 (basal), and averaged E1 to E12 with CN CSA on magnetic resonance imaging was performed. A Pearson correlation of the ART/AutoART ECAP thresholds/slopes for E2/E6/E10 and the averaged electrodes E1 to E12 showed a significant correlation. The CN CSA did not correlate significantly with the averaged ART/AutoART ECAP thresholds/slopes across all 12 electrodes. AutoART provides reliable measurements and is therefore a suitable alternative to ART. No significant influence of CN CSA on ECAP thresholds/slopes was observed. A predictive evaluation of the success of ECAP measurements based on CN CSA for a clinical setting cannot be made according to the present data.

Prioritization of Lane-Specific Traffic Jam Detection for Automotive Navigation Framework Utilizing Suddenness Index and Automatic Threshold Determination

Prioritization of Lane-Specific Traffic Jam Detection for Automotive Navigation Framework Utilizing Suddenness Index and Automatic Threshold Determination

Determination of Monitoring Control Value for Concrete Gravity Dam Spatial Deformation Based on POT Model

Deformation can directly reflect the working behavior of the dam, so determining the deformation monitoring control value can effectively monitor the safety of dam operation. The traditional dam deformation monitoring control value only considers the single measuring point. In order to overcome the limitation, this paper presents a new method to determine the monitoring control value for concrete gravity dam based on the deformations of multi-measuring points. A dam’s comprehensive deformation displacement is determined by the measured values at different measuring points on the positive inverted vertical line and the corresponding weight of each measuring point. The projection pursuit method (PPM) combined with the grey wolf optimization (GWO) algorithm is used to determine the weight of each measuring point according to the spatial correlation distribution characteristics of dam deformation. The peaks over threshold (POT) model based on the extreme value theory is adopted to determine the monitoring control value with the obtained dam comprehensive deformation displacement. In addition, the POT model is improved with the automatic threshold determination method based on the criterion in probability theory and the GWO algorithm, which can avoid subjectivity and randomness in determining the threshold. The results of the engineering application show the feasibility and applicability of the proposed method.

Mapping of small water bodies with integrated spatial information for time series images of optical remote sensing

Small water bodies and their temporal changes are, especially in urban areas, closely related to people’s daily life and they have an impact on the living environment. For small water bodies mapping with optical remote sensing images, it is challenging to establish a balance between reducing incorrect water detection and increasing the integrity of water extraction. For time-series application, the temporal variability of the spectral information is also challenging for the widely used threshold methods, which are frequently solely based on spectral analysis. In this work we propose a spatial information-integrated small water bodies mapping (SWM) method to achieve a complete and accurate extraction and temporal change monitoring of small water bodies in complex urban environments. Our strategy is to make use of the spatial contextual information to account for the indistinguishability of small water bodies in spectral information. The roughness of the water index is calculated to enhance the contrast between water bodies and other thematic classes eventually present in the imagery. The proposed SWM was applied to different water indexes with an automatic threshold determination. We tested the effectiveness of the proposed algorithm using Landsat and Sentinel-2 multispectral data from three different urban environments (Shanghai, Guangzhou, and Wuhan in China) which include a variety of river courses and lakes. Nantan Lake of China is selected as a representative experimental area to test the SWM method by generating the inter- and intra-year water results. Overall accuracy (OA), F1 score (F1), producer’s accuracy (PA), and user’s accuracy (UA) were used to quantitatively evaluate the accuracy of the algorithm. Compared with the four state-of-the-art water detection methods (supervised random forest classification, hierarchical clustering, multi-band threshold, and modified normalized difference water index (MNDWI)), the proposed SWM algorithm achieves better water extraction performance. Small water bodies are found to be extracted more completely and incorrect water extractions are alleviated. The overall accuracy of the SWM algorithm achieves an average of approx. 97% (OA) and 0.95 (F1). The long-time sequence (from 2007 to 2021) and the short-time interval (monthly results of the year 2020) of the water extraction results by the SWM agree well with the ground truth data. The mean absolute area deviations between the water body extraction results of the SWM algorithm and ground truth is significantly smaller than that of the Global Surface Water dataset developed by the European Commission's Joint Research Centre (3.5% vs 49.0% for annual results and 6.0% vs 35.0% for monthly results).

Reversible Data Hiding of Digital Image Based on Pixel Combination Algorithm

In order to improve the security effect of image information, this paper studies the reversible information hiding of the digital images combined with the pixel combination algorithm and proposes an improved simulated annealing algorithm using the incremental calculation method of statistical functions. Moreover, according to the gray gradient information contained in the image, this paper proposes an automatic threshold determination algorithm suitable for the unimodal gray distribution images and uses this algorithm to complete the threshold determination and binary segmentation of all images. In addition, this paper optimizes the model by transforming the isolated pores inside the model and removing the isolated matrix area. Through comparative experiments, it can be seen that the reversible information hiding method for digital images based on the pixel combination algorithm proposed in this paper has a good image information confidentiality effect.

Garland chrysanthemum consumption ameliorates age-related hearing loss in C57BL/6 mouse; model system to explore hearing loss prevention foods in a short period.

Garland chrysanthemum (Glebionis coronaria L.) is an antioxidant-rich leafy vegetable. We found that garland chrysanthemum consumption ameliorated age-related hearing loss (AHL) in C57BL/6J mice, an early onset model. We also found that AHL progression was significantly ameliorated by three of ten products. Metabolome analysis of the 10 products using nuclear magnetic resonance (NMR) spectroscopy indicated that phytosterols may be involved in the amelioration of AHL. However, the direct inhibitory effect of phytosterol mixture on mouse AHL progression was not identified. These results suggest that garland chrysanthemum consumption delays AHL development in mice and its efficiency varies depending on the source of the product. Our findings also suggest that phytosterol content in garland chrysanthemum functions as an evaluation marker for the efficiency. Furthermore, to accelerate the search for foods that prevent AHL, we have used these data to develop an automatic threshold determination method for auditory brainstem response using machine learning.

Reproduction of the Marine Debris Distribution in the Seto Inland Sea Immediately after the July 2018 Heavy Rains in Western Japan Using Multidate Landsat-8 Data

Understanding the spatiotemporal environment of the ocean after a heavy rain disaster is critical for satellite remote sensing research and disaster prevention. We attempted to reproduce changes in marine debris distributions using multidate data of Landsat-8 spectral reflectance acquired immediately after a heavy rain disaster in western Japan in July 2018. Data from cleaning ships were used for screening the marine debris area. As most of the target marine debris consisted of plant fragments, a method based on the corrected floating algae index (cFAI) was applied to Landsat-8 data. Data from cleaning ships clarify that most of the marine debris accumulated in the waters in the northern part of Aki Nada, a part of the Seto Inland Sea. The spectral characteristics of the corresponding marine debris spectral reflectance obtained from the Landsat-8 data were explained by the FAI with band 5 (central wavelength: 865 nm) as the maximum value. Unlike traditional FAI, cFAI eliminated the effect of background water turbidity. The Otsu method was effective for the automatic threshold determination for cFAI. Although Landsat-8 data have limited spatial resolution and observation frequency, these data were useful for understanding marine debris distribution after a heavy rain disaster.

Real-time threshold determination of auditory brainstem responses by cross-correlation analysis

SummaryAuditory brainstem response (ABR) serves as an objective indication of auditory perception at a given sound level and is nowadays widely used in hearing function assessment. Despite efforts for automation over decades, ABR threshold determination by machine algorithms remains unreliable and thereby one still relies on visual identification by trained personnel. Here, we described a procedure for automatic threshold determination that can be used in both animal and human ABR tests. The method terminates level averaging of ABR recordings upon detection of time-locked waveform through cross-correlation analysis. The threshold level was then indicated by a dramatic increase in the sweep numbers required to produce “qualified” level averaging. A good match was obtained between the algorithm outcome and the human readouts. Moreover, the method varies the level averaging based on the cross-correlation, thereby adapting to the signal-to-noise ratio of sweep recordings. These features empower a robust and fully automated ABR test.

Comparison of automated and traditional ECAP recording approaches in clinical practice

Objective The traditional method of recording electrically evoked compound action potentials (ECAPs), as implemented in the MAESTRO clinical software (standard ART), requires manual adjustments during threshold determination through a specialist. The “FineGrain” research tool (FineGrain RT) uses a continuous stimulation paradigm combined with automatic ECAP threshold determination. The aim of this study was to compare the FineGrain RT with standard ART. Design ECAPs were recorded with standard ART and the FineGrain RT in paediatric cochlear implant recipients. Different stimulation rates were used for FineGrain ECAP recordings (40, 60, and 76 Hz). Study sample Thirteen children (6 − 19 years) participated in this study - nine were bilaterally and four unilaterally implanted, resulting in a total of twenty-two implanted ears. Results ECAP threshold determination success rates were similar between the two approaches (92% and 89%) and ECAP thresholds correlated well (r: 0.94, p < 2.2e–16) with average ART thresholds being lower than FineGrain RT thresholds. FineGrain stimulation with different stimulation rates did not have a significant effect on ECAP thresholds but ECAP thresholds at medial and apical contacts were lower compared to basal contacts. Conclusions TheFineGrain research approach is a reliable replacement for standard ART in clinical practice.

Challenges Using Droplet Digital PCR for Environmental Samples

Droplet digital polymerase chain reaction (ddPCR) is a method used to detect and quantify nucleic acids even when present in exceptionally low numbers. While it has proven to be valuable for clinical studies, it has failed to be widely adopted for environmental studies but despite some limitations, ddPCR may represent a better option than classical qPCR for environmental samples. Due to the complexity of the chemical and biological composition of environmental samples, protocols tailored to clinical studies are not appropriate, and results are difficult to interpret. We used environmental DNA samples originating from field studies to determine a protocol for environmental samples. Samples included field soils which had been inoculated with the soil fungus Rhizophagus irregularis (environmental positive control), field soils that had not been inoculated and the targeted fungus was not naturally present (environmental negative control), and root samples from both field categories. To control for the effect of soil inhibitors, we also included DNA samples of an organismal control extracted from pure fungal spores (organismal positive control). Finally, we included a no-template control consisting only of the PCR reaction reagents and nuclease free water instead of template DNA. Using original data, we examined which factors contribute to poor resolution in root and soil samples and propose best practices to ensure accuracy and repeatability. Furthermore, we evaluated manual and automatic threshold determination methods and we propose a novel protocol based on multiple controls that is more appropriate for environmental samples.

Optimal identification of H ii regions during reionization in 21-cm observations

The ability of the future low frequency component of the Square Kilometre Array radio telescope (SKA-Low) to produce tomographic images of the redshifted 21-cm signal will enable direct studies of the evolution of the sizes and shapes of ionized regions during the Epoch of Reionization. However, a reliable identification of ionized regions in noisy interferometric data is not trivial. Here, we introduce an image processing method known as superpixels for this purpose. We compare this method with two other previously proposed ones, one relying on a chosen threshold and the other employing automatic threshold determination using the K-Means algorithm. We use a correlation test and compare power spectra and bubble size distributions to show that the superpixels method provides a better identification of ionized regions, especially in the case of noisy data. We also describe some possible additional applications of the superpixel method, namely the derivation of the ionization history and constraints on the source properties in specific regions.

Flow feature detection for grid adaptation and flow visualization

Adaptive grid refinement/coarsening is an important method for achieving increased accuracy of flow simulations with reduced computing resources. Further, flow visualization of complex 3-D fields is a major task of both computational fluid dynamics (CFD), as well as experimental data analysis. A primary issue of adaptive simulations and flow visualization is the reliable detection of the local regions containing features of interest. A relatively wide spectrum of detection functions (sensors) is employed for representative flow cases which include boundary layers, vortices, jets, wakes, shock waves, contact discontinuities, and expansions. The focus is on relatively simple sensors based on local flow field variation using 3-D general hybrid grids consisting of multiple types of elements. A quantitative approach for sensors evaluation and comparison is proposed and applied. It is accomplished via the employment of analytic flow fields. Automation and effectiveness of an adaptive grid or flow visualization process requires the reliable determination of an appropriate threshold for the sensor. Statistical evaluation of the distributions of the sensors results in a proposed empirical formula for the threshold. The qualified sensors along with the automatic threshold determination are tested with more complex flow cases exhibiting multiple flow features.

CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

BackgroundA gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale.ResultsHere, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package.ConclusionsThis new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1324-y) contains supplementary material, which is available to authorized users.

A new copy move forgery detection technique with automatic threshold determination

Ensuring authenticity of images has become an important issue recently. Copy move forgery is one of the most common tampering techniques used to modify images. Copy move forgery detection techniques in the literature divide the image into overlapping blocks and use various techniques to extract features from the blocks. Similarity between the feature vectors is a clue about the forgery. However, these techniques use a predefined threshold to test the similarity. Test images with different characteristics require various threshold values. Determination of the best threshold value can be troublesome because the range of the feature vector elements’ cannot be predetermined. Therefore, many experiments must be realized to find the best threshold value. In this work, we utilize DCT-phase terms to restrict the range of the feature vector elements’ and Benford’s generalized law to determine the compression history of the image under test. The method uses element-by-element equality between the feature vectors instead of Euclidean distance or cross correlation and utilizes compression history to determine the threshold value for the current test image automatically. Experimental results show that the method can detect the copied and pasted regions under different scenarios and gives higher accuracy ratios/lower false negative compared to similar works.

Laser-based measuring method for mean joint faulting value of concrete pavement

To realize the critical assessment of concrete joint faulting, a laser-based 3D detection system (Laser-based Joint Faulting Meter, LJFM) was designed and a calculation method was proposed. The 3D information of joint faulting was obtained based on laser triangulation method. Automatic threshold determination method and mean joint faulting value calculation method were proposed based on the double peak characteristic of joint faulting 3D height histogram. To verify the precision and accuracy of the LJFM, indoor and field experiments were designed and conducted. Repeated experiments of simulated joint faulting in indoor experiment show that measurement results of the LJFM has lower coefficients of variation, better reproducibility and higher stability than that of the Level. In indoor and field experiments of different joint faulting, the coefficient of determination between the LJFM and the Level are 0.944 and 0.958 separately while the correlation coefficients between them are 0.9761and 0.979 (both significant at p<0.05 level), respectively, indicating the good repeatability of the LJFM and the high correlation of the two methods. Experimental results indicate that measuring mean joint faulting value using LJFM has high stability and accuracy.

The development and application of an automatic boundary segmentation methodology to evaluate the vaporizing characteristics of diesel spray under engine-like conditions

Studying the vaporizing characteristics of diesel spray could greatly help to reduce engine emission and improve performance. The high-speed schlieren imaging method is an important optical technique for investigating the macroscopic vaporizing morphological evolution of liquid fuel, and pre-combustion constant volume combustion bombs are often used to simulate the high pressure and high temperature conditions occurring in diesel engines. Complicated background schlieren noises make it difficult to segment the spray region in schlieren spray images. To tackle this problem, this paper develops a vaporizing spray boundary segmentation methodology based on an automatic threshold determination algorithm. The methodology was also used to quantify the macroscopic characteristics of vaporizing sprays including tip penetration, near-field and far-field angles, and projected spray area and spray volume. The spray boundary segmentation methodology was realized in a MATLAB-based program. Comparisons were made between the spray characteristics obtained using the program method and those acquired using a manual method and the Hiroyasu prediction model. It is demonstrated that the methodology can segment and measure vaporizing sprays precisely and efficiently. Furthermore, the experimental results show that the spray angles were slightly affected by the injection pressure at high temperature and high pressure and under inert conditions. A higher injection pressure leads to longer spray tip penetration and a larger projected area and volume, while elevating the temperature of the environment can significantly promote the evaporation of cold fuel.

Abstract 14908: The Success Rate of Automatic Pacing Threshold Determination Functions Differ among the Brands: What Was the Best Brand in a Far-East Single Center?

Introduction: Reliable automatic pacing threshold determination functions offer a reduced follow-up examination time and safe remote monitoring. Further, the success rate and accuracy of the automatic pacing threshold determination function have not been sufficiently clarified. Methods: We evaluated 456 patients (male/female: 269/187, age: 70.4±13.3 years, pacemakers/defibrillators: 341/115) with cardiac implantable devices that had an automatic pacing threshold measurement function (the atrium and ventricle/ ventricle only: 298/158). We measured their pacing thresholds with both the automatic and manual methods at periodic device examination visits. Patients who had a high threshold (&gt;4.0V/0.4ms) or out-of-range lead impedance (&gt;2000 or &lt;200Ω) were excluded from the analysis. Results: An automatic pacing threshold was obtained successfully in 206/274 (75.2%) patients in the atrium and in 392/443 (88.5%) in the ventricle. The automatic pacing threshold differed from the manual threshold by more than 1.0mV at the same pulse width in 12 (4.0%) patients in the atrium and in 5 (1.1%) in the ventricle. The success rate of the automatic pacing threshold determination differed depending on which generator manufacturer was used. The success rate for each manufacturer (Medtronic, St. Jude Medical, Biotronik and Sorin) was 167/173 (96.5%), 9/64 (14.1%), 30/37 (81.1%), and 0/0 in the atrium, and 223/224 (99.6%), 79/102 (77.5%), 68/85 (80.0%), and 22/32 (68.8%) in the ventricle, respectively. Regarding the success rate, Medtronic devices were superior to the others in both the atrium and ventricle (P&lt;0.001-P=0.039). St. Jude Medical devices were inferior to the others in the atrium (p&lt;0.001). There were no other significant factors affecting the success rate. The correlation between the pacing threshold measured by the automatic method and that by the manual method was significant in the atrium (r=0.558, P&lt;0.001) and ventricle (r=0.779, P&lt;0.001). Conclusions: The success rate of the automatic pacing threshold determination depended on which generator manufacturer was used. The measurable threshold values using the automatic method were acceptably correlated with those measured by the manual method.

Preoperative mapping of the sensorimotor cortex: comparative assessment of task-based and resting-state FMRI.

Resting state fMRI (rs-fMRI) has recently been considered as a possible complement or alternative to task-based fMRI (tb-fMRI) for presurgical mapping. However, evidence of its usefulness remains scant, because existing studies have investigated relatively small samples and focused primarily on qualitative evaluation. The aim of this study is to investigate the clinical usefulness of rs-fMRI in the context of presurgical mapping of motor functions, and in particular to determine the degree of correspondence with tb-fMRI which, while not a gold-standard, is commonly used in preoperative setting. A group of 13 patients with lesions close to the sensorimotor cortex underwent rs-fMRI and tb-fMRI to localize the hand, foot and mouth motor areas. We assessed quantitatively the degree of correspondence between multiple rs-fMRI analyses (independent-component and seed-based analyses) and tb-fMRI, with reference to sensitivity and specificity of rs-fMRI with respect to tb-fMRI, and centre-of-mass distances. Agreement with electro-cortical stimulation (ECS) was also investigated, and a traditional map thresholding approach based on agreement between two experienced operators was compared to an automatic threshold determination method. Rs-fMRI can localize the sensorimotor cortex successfully, providing anatomical specificity for hand, foot and mouth motor subregions, in particular with seed-based analyses. Agreement with tb-fMRI was only partial and rs-fMRI tended to provide larger patterns of correlated activity. With respect to the ECS data available, rs-fMRI and tb-fMRI performed comparably, even though the shortest distance to stimulation points was observed for the latter. Notably, the results of both were on the whole robust to thresholding procedure. Localization performed by rs-fMRI is not equivalent to tb-fMRI, hence rs-fMRI cannot be considered as an outright replacement for tb-fMRI. Nevertheless, since there is significant agreement between the two techniques, rs-fMRI can be considered with caution as a potential alternative to tb-fMRI when patients are unable to perform the task.

Self-adaptive partial discharge signal de-noising based on ensemble empirical mode decomposition and automatic morphological thresholding

This paper proposes a self-adaptive technique for partial discharge (PD) signal denoising with automatic threshold determination based on ensemble empirical mode decomposition (EEMD) and mathematical morphology. By introducing extra noise in the decomposition process, EEMD can effectively separate the original signal into different intrinsic mode functions (IMFs) with distinctive frequency scales. Through the kurtosis-based selection criterion, the IMFs embedded with PD impulses can be extracted for reconstruction. On the basis of mathematical morphology, an automatic morphological thresholding (AMT) technique is developed to form upper and lower thresholds for automatically eliminating the residual noise while maintaining the PD signals. The results on both simulated and real PD signals show that the above PD denoising technique is superior to wavelet transform (WT) and conventional EMD-based PD de-noising techniques.

Self-adaptive partial discharge signal de-noising based on ensemble empirical mode decomposition and automatic morphological thresholding

This paper proposes a self-adaptive technique for partial discharge (PD) signal denoising with automatic threshold determination based on ensemble empirical mode decomposition (EEMD) and mathematical morphology. By introducing extra noise in the decomposition process, EEMD can effectively separate the original signal into different intrinsic mode functions (IMFs) with distinctive frequency scales. Through the kurtosis-based selection criterion, the IMFs embedded with PD impulses can be extracted for reconstruction. On the basis of mathematical morphology, an automatic morphological thresholding (AMT) technique is developed to form upper and lower thresholds for automatically eliminating the residual noise while maintaining the PD signals. The results on both simulated and real PD signals show that the above PD denoising technique is superior to wavelet transform (WT) and conventional EMD-based PD de-noising techniques.