Peak Noise Research Articles

Performance evaluation of a small-animal PET scanner with 213 mm axis using NEMA NU 4-2008.

Long-axis positron emission tomography (PET) has emerged as one of the recent research directions in PET due to its ability to significantly enhance sensitivity and counting performance for low-dose imaging, rapid imaging, and whole-body dynamicimaging. The PET system presented in this study is a long-axis animal PET based on lutetium-yttrium orthosilicate and silicon photomultiplier, designed for whole-body imaging in rats. It features a diameter of 143 mm and an axial length of 213.3 mm. This study evaluated the performance of this PET system in accordance with the National Electrical Manufacturers Association (NEMA) NU 4-2008standards. The performance evaluation was conducted according to the NEMA NU 4-2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction (SF) and image quality. In addition, a rat imaging study was conducted to assess the imaging capability of this PETsystem. The average energy resolution of the PET system was 12.87%, the average coincidence timing resolution was 751 ps. The FWHM of spatial resolution reconstructed by filtered back projection and 3D-OSEM-PSF algorithm at 5 mm radial offset from the axial center were 1.65 and 0.88 mm. The peak absolute sensitivity measured by a point source at the center of the field of view was evaluated as 6.71% (361-661keV) and 10.31% (250-750 keV). For the mouse-like phantom, the SF was 11.0% and the peak noise equivalent counting rate (NECR) was 1193 kcps at 94.2 MBq (2.54 mCi). For the rat-like phantom, the SF was 26.8% and the NECR was 682.5 kcps at 78.6 MBq (2.12 mCi). The performance measurement results demonstrate that this PET system exhibits high sensitivity and count rate performance, making it potential for high-quality whole-body dynamic imaging ofrats.

Analysis and suppression research of high lift device noise based on large aeroacoustic wind tunnel test

The exterior noise of large aircrafts is an important aspect for the airworthiness certification. The high-lift device is one of the key noise sources for large aircrafts, thus the analysis and reduction of high-lift device noise is important and meaningful. Based on the 5.5m×4.0m Aeroacoustic Wind Tunnel and a half model for the aeroacoustic study of large scale aircrafts, the high-lift device noise properties were studied experimentally. First, the experimental platform, the test model, the test system and noise reduction design were introduced. Then, based on the experimental results, the noise characteristics of the high-lift devices were analyzed. The effects on the noise from the angle of attack and the wind speed were compared. The effects on the high-lift device noise from the noise reduction design on slat and flap were investigated. The results show that, the high-lift device noise has a broad frequency spectrum, with some peak frequency components. As the angle of attack is increased, the noise of the model is generally increased in the medium to high frequency range. With the wind speed increased, the noise is increased dramatically, and the frequency spectra keep a good similarity. The peak noise is suppressed by the noise reduction design.

Delayed-X harmonic synthesizer cancelling narrow bandpass noises by control signals via aural cartilage conduction

When a transducer is put on an aural cartilage, the transmitted vibration generates sound in the external auditory canal (i.e., cartilage conduction). A hearing device based on the cartilage conduction does not need occluding the external auditory canal. When an active noise control can adapt only to unwanted noise, the device enables natural conversations with unprocessed voice in the noisy environment (selective cancelation). To accomplish the selective cancelation, we proposed delayed-X harmonics synthesizer (DXHS) algorithm to minimize the damage for the speech quality. A target noise in this study was bandpass noise through a gammatone filter (center frequency: 500 Hz) overlapping the speech spectrum. After tracing the spectral envelope of the noise by using linear predictive coding (LPC), the DXHS outputted five pure tones distributed around the peak of envelope, and each step size parameter was adjusted according to the amplitude of the envelope. As results, our proposed method showed the noise reduction of 11.3 dB maintaining the speech quality in the computer simulations. During the adaptation, the step size adjustment enabled round off the spectral peak of the bandpass noise to avoid sharpening it.

Sound quality improvement on industrial products

Even with efforts to reduce the noise level (dB) of industrial products, some people remain dissatisfied with the sound of products due to annoyances remained. Annoyance is closely related to the sound quality (SQ), especially in quiet environments such as hospitals and laboratories, it is essential to improve the sound quality (comfort of listening) of products. We defined a method for evaluating the sound quality of industrial products that we handle using both existing and developed sound quality indices that focus on the high-pitched sound, the prominent peak noise, the rough sound and the beat/moan noise, and improved our actual products based on the method. In this paper, we introduce the evaluation method and the sound quality improvement in actual products, including one of research activities that contributes to the business unit and has the potential to create future customer value.

Effects of the earplug and external ear hardness of the direct transmissions induced by high-level impulse noises

The performances of Hearing Protection Devices (HPD) facing high-level impulse noises is limited by the transmission through the protector. This transmission can be evaluated by measuring the earplug's displacement along the ear canal axis. Previous measurements highlighted a displacement proportional to the peak acoustic pressure in the protected ear canal. To better understand the consequences on the HPD performances, this evaluation requires to be extended. Thus, various configurations are studied with Acoustic Test Fixture (ATF) external ears and earplugs of low and medium hardness. The earplug's peak displacements have been measured with a laser-vibrometer and the acoustic pressure with the ATF microphone. The impulse waves employed to excite the earplugs ranged from 150 dB to 180 dB peak. A medium hardness earplug inserted in a low hardness ear led to the worst performances with a plug displacement of 200 µm and a peak noise reduction of 17.8 dB(SPL) for an impulse noise of 177 dB(SPL). For the best case, a maximum displacement of 66 µm and peak noise reduction of 28.8 dB(SPL) have been measured. These results suggest new perspectives to improve the HPDs but also their evaluation through the choice of judicious ATF materials that conform to biological tissues.

Participative pilot study at the vicinity of airports for the construction of a noise point counter integrating instantaneous annoyance at overflight

Current regulations on transport noise are based on energetic acoustic indicators that do not adequately reflect the intensity and repetitive nature of noise peaks, particularly for aircraft overflights or rail traffic. The public debate on these issues therefore often centres on the questioning of these indicators, which are deemed to be inadequate to reflect the annoyance caused to local populations, particularly in a context of increasing traffic. Bruitparif suggests exploring a noise events counter, the Noise Point Counter (NPC), based on existing NAX indicators but freeing itself from the threshold effect, which is a drawback to their use. The idea is to count the number of noise events, weighting each event according to the level of instantaneous annoyance it is likely to generate for local residents. To make progress on the feasibility of developing such an indicator and to confirm its relevance, Bruitparif is proposing to carry out a pilot study on three selected overflown areas in the Île-de-France region, involving around thirty local residents on each occasion. The paper will present the principle behind the creation of this new indicator as well as the pilot study protocol.

Improving knowledge of the acoustic factors involved in railway noise annoyance: first results of a pilot field survey of sixty-two local residents

Railway transportation contributes to the objectives of decarbonization but also generates negative externalities, including noise. Energy noise indicators used to characterize population exposure do not adequately reflect the repetitive nature of railway noise peaks. The GENIFER pilot study aims to test a protocol designed to characterize railway noise events according to the instantaneous perceived annoyance when the train is passing, in order to improve understanding of the influence of acoustic factors on annoyance. The first phase of the survey was carried out in 2023 among 62 residents of a pilot site. An electronic device was used to collect around 5,000 ratings, ranging from 1 to 10, assessing the instantaneous annoyance induced by train noise at passing trains. The site instrumentation included sixteen sound level meters and two video recording systems, enabling annoyance ratings to be associated with the acoustic characteristics of railway noise events. A questionnaire aimed at identifying co-determinants of long-term annoyance was also administered to participants. Feedback on the field implementation of this survey and initial results concerning acoustic measurements, instantaneous annoyance ratings and questionnaire responses will be presented.

Research on the design and noise reduction performance of periodic noise barriers based on nested structure

The rapid development of highway transportation has led to a gradual deterioration of the sound environment along highways. The theory of periodic structures provides a new approach for the design of traffic noise barriers. However, the lack of practical numerical models and on-site experimental validation has hindered the widespread application of periodic structure sound barriers. This study investigates the noise reduction performance of nested structure periodic sound barriers. Results from semi-anechoic chamber tests demonstrate excellent wave attenuation at the air gap of the barrier, achieving a peak noise reduction of 16 dB without the addition of any sound-absorbing materials or treatment measures, particularly at local peaks in the highway noise spectrum. To enhance the noise reduction performance of nested structure periodic sound barriers, three optimization measures were explored: filling sound-absorbing materials inside the scattering elements, adding micro-perforated panels, and their combined effects. The results indicate that both porous sound-absorbing materials and micro-perforated panels can improve noise reduction effectiveness, especially outside the air gap. In the optimization design of nested structure periodic sound barriers, adding porous sound-absorbing materials inside the micro-perforated panels effectively enhances noise reduction within the air gap. Considering the abundance of abandoned w-beam guardrails in highway projects, which also meet the requirements of scattering elements, this study proposes the use of abandoned w-beam guardrails as scattering elements. This approach aligns with principles of cost-effectiveness and environmental sustainability, and it provides design guidance to promote the application of nested structure periodic sound barriers in traffic noise control.

Quieting the neonatal intensive care unit: A quality improvement initiative.

The neonatal intensive care unit (NICU) is vital for preterm infants but is often plagued by harmful noise levels. Excessive noise, ranging from medical equipment to conversations, poses significant health risks, including hearing impairment and neurodevelopmental issues. The American Academy of Pediatrics recommends strict sound limits to safeguard neonatal well-being. Strategies such as education, environmental modifications, and quiet hours have shown to reduce noise levels. However, up to 60% of the noises remain avoidable. High noise exposure exacerbates physiological disturbances, impacting vital functions and long-term neurological outcomes. Effective noise reduction in the NICU is crucial for promoting optimal neonatal development. To measure the sound levels in a NICU and reduce ambient sound levels by at least 10% from baseline. A quasi-experimental quality improvement project was conducted over 4 mo in a 20-bed level 3 NICU in a tertiary care medical college. Baseline noise levels were recorded continuously using a sound level meter. The interventions included targeted education, environmental modifications, and organizational changes, and were implemented through three rapid Plan-Do-Study-Act (PDSA) cycles. Weekly feedback and monitoring were conducted, and statistical process control charts were used for analysis. The mean noise values were compared using the paired t-test. The baseline mean ambient noise level in the NICU was 67.8 dB, which decreased to 50.5 dB after the first cycle, and further decreased to 47.4 dB and 51.2 dB after subsequent cycles. The reduction in noise levels was 21% during the day and 28% at night, with an overall decrease of 25% from baseline. The most significant reduction occurred after the first PDSA cycle (mean difference of -17.3 dB, P < 0.01). Peak noise levels decreased from 110 dB to 88.24 dB after the intervention. A multifaceted intervention strategy reduced noise in the NICU by 25% over 4 months. The success of this initiative emphasizes the significance of comprehensive interventions for noise reduction.

Identifying the electromagnetic counterparts of LISA massive black hole binaries in archival LSST data

ABSTRACT LSST will catalogue the light curves of up to 100 million quasars. Among these there can be $\sim$100 ultra-compact massive black hole (MBH) binaries, whose gravitational waves (GWs) can be detected 5–15 yr later by LISA. Here, we assume such a LISA detection occurred, and assess whether or not its electromagnetic (EM) counterpart can be identified as a periodic quasar in archival LSST data. We use the binary’s properties derived from the LISA waveform, including the evolution of its orbital frequency, its total mass, distance, and sky localization, to predict the redshift, magnitude, and historical periodicity of the quasar expected in the LSST data. We then use Monte Carlo simulations to compute the false alarm probability (FAP), i.e. the number of quasars in the LSST catalogue matching these properties by chance, based on the (extrapolated) quasar luminosity function, the cadence of LSST, and intrinsic ‘damped random walk’ quasar variability. We analyse four fiducial LISA binaries, with masses and redshifts of $(M_{\rm bin}/{\rm M_{\odot }},z) = (3\times 10^5,0.3)$, $(3\times 10^6,0.3)$, $(10^7,0.3)$, and $(10^7,1)$. While noise and aliasing due to LSST’s cadence produces false periodicities by chance, we find that the frequency chirp of the LISA source during the LSST observations washes out these noise peaks and allows the genuine source to stand out in appropriately scaled Lomb–Scargle periodograms. We find that all four fiducial binaries can be uniquely identified, with ${\rm FAP}\lt 10^{-5}$, a week or more before merger. This should enable follow-up EM observations targeting individual EM counterparts during their inspiral stage.

Artificial Amacrine Retinal Circuits.

Event-based imaging represents a new paradigm in visual information processing that addresses the speed and energy efficiency shortcomings inherently present in the current complementary metal oxide semiconductor-based machine vision. Realizing such imaging systems has previously been sought using very large-scale integration technologies that have complex circuitries consisting of many photodiodes, differential amplifiers, capacitors, and resistors. Here, we demonstrate that event-driven sensing can be achieved using a simple one-resistor, one-capacitor (1R1C) circuit, where the capacitor is modified with colloidal quantum dots (CQDs) to have a photoresponse. This sensory circuit emulates the motion-tracking function of the biological retina, in which the amacrine cells in the bipolar-to-ganglion synaptic pathway produce a transient spiking signal only in response to changes in light intensity but remain inactive under constant illumination. When extended to a 2D imaging array, the individual sensors work independently and output signals only when a change in the light intensity is detected; hence, the concept of the frame in image processing is thereby removed. In this work, we present the fabrication and characterization of a CQD photocapacitor-based 1R1C circuit that has a spectral response at 1550 nm in the short-wave infrared (SWIR). We report on the key performance parameters including peak responsivity, noise, and optical noise equivalent power and discuss the operating mechanism that is responsible for spiking responses in these artificial retinal circuits. The present work sets the foundation for expanding the bioinspired vision sensor capability toward midwave infrared (MWIR) and long-wave infrared (LWIR) spectral regions that are invisible to human eyes and mainstream semiconductor technologies.

Identification of blood at simulated crime scenes using silver nanoparticles with SERS.

The analysis of substances and samples obtained from a crime scene is very important in solving forensic cases. To determine the variables involved in a crime and to expedite the investigation process, the rapid analysis of body fluids in small quantities and within environments containing diverse components is particularly necessary. For this reason, it is of great importance to analyze biological fluids with rapid, noncontaminating, nondestructive, low-cost, and accurate techniques. In recent years, with advancements in laser technology, spectroscopic methods have been introduced as analytical techniques in forensic medicine and chemical studies. This study focuses on surface-enhanced Raman spectroscopy (SERS) to demonstrate the detection of blood samples in simulated crime scenes. To minimize the background signal from fluorescent biomolecules in blood, dilution was performed with two different components and Raman analysis was performed for four different concentrations of blood. In general, a decrease in noise in the spectra was observed as the blood was diluted. Crime scenes consisting of pure blood, blood diluted with ethanol and distilled water (1:2, 1:4, and 1:8), a blood-mineral water mixture, a blood-cherry juice mixture, and silver nanoparticle-added mixtures were simulated, and their spectra were examined. Chemometric analyses of the data were performed. Despite high noise and low peak intensities, blood-identifying signals were detected when examining different blood concentrations. It was observed that silver nanoparticles provided high enhancement of blood peaks thanks to their strong plasmonic properties.

MAP-based blind infrared spectral deconvolution via modified total variation regularization for mixture identification

Infrared (IR) spectral signals have problems with random noise and overlapping of adjacent peaks. To address these issues, we proposed a novel infrared spectral reconstruction model with improved total variation. The maximum a posteriori theory (MAP) is introduced to build the signal reconstruction model for the latent infrared spectrum. The proposed model can remove the random spectral noise and generate new peaks. In the MAP architecture, the prior probability is modeled as an improved total variation constraint, the spectral noise based on the Gaussian distribution is constructed for the likelihood probability distribution. Then, the proposed infrared spectral signal model is optimized by the famous split Bregman iteration approach. The high-quality infrared spectrum and instrument function can be estimated from the simulated and real spectral signals using the proposed model. The compared experiments show the good performance in suppressing spectral noise and splitting overlap peaks.

Modeling and analysis of crosstalk induced effects in graphene-carbon nanotube composite interconnects

This paper proposes an equivalent circuit model for two-line coupled multilayer graphene nanoribbon - single-wall carbon nanotube (MLGNR-SWCNT) composite interconnects (MSCs), incorporating the effects of coupling capacitance and mutual inductance. We also examine the temperature-dependent crosstalk effect on the victim line of MSCs in the time domain using decoupling techniques and the ABCD parameter matrix approach. This analysis is conducted at the global level of 7 nm, 14 nm, and 22 nm technology nodes, comparing the performance of MSCs with MLGNR, SWCNT, and copper (Cu) interconnects, validated through HSPICE simulations. Our results reveal that the crosstalk delay of all interconnects induced by dynamic crosstalk exhibits superior performance in the in-phase crosstalk mode compared to the out-of-phase mode at room temperature. In particular, MSCs demonstrate less crosstalk delay in both crosstalk modes compared to SWCNT and Cu interconnects. In addition, we analyze the crosstalk delay of the victim line for two-line coupled MSCs at varying temperatures in out-of-phase crosstalk mode, comparing them with MLGNR, SWCNT, and Cu interconnects. Simulation results indicate that the crosstalk delay is temperature-dependent, increasing with rising temperatures, and the crosstalk delay of MSCs is the least of all interconnects. Furthermore, we investigate the crosstalk noise of MSCs induced by functional crosstalk at different temperatures, comparing it with MLGNR, SWCNT, and Cu interconnects. It is observed that the crosstalk noise peak remains constant with temperature changes across all interconnects; however, the holding time and width of crosstalk noise increases with rising temperatures and MSCs have the least crosstalk noise peak and crosstalk noise width of all interconnects. Also, numerical results exhibit that reducing interconnect temperature, SWCNT diameter, and edge roughness of MLGNR are effective strategies to diminish the crosstalk delay of MSCs. In addition, increasing line spacing is identified as an effective method to reduce crosstalk noise peak of MSCs of different lengths. The proposed model results show excellent agreement with HSPICE simulation data. Therefore, our analysis of crosstalk effect manifests that MLGNR-SWCNT composite can be a promising material to replace SWCNT and copper as an ideal material for global interconnect applications in thermally variable environments.

ADPSCAN: Structural Graph Clustering with Adaptive Density Peak Selection and Noise Re-Clustering

Structural graph clustering is a data analysis technique that groups nodes within a graph based on their connectivity and structural similarity. The Structural graph clustering SCAN algorithm, a density-based clustering method, effectively identifies core points and their neighbors within areas of high density to form well-defined clusters. However, the clustering quality of SCAN heavily depends on the input parameters, ϵ and μ, making the clustering results highly sensitive to parameter selection. Different parameter settings can lead to significant differences in clustering results, potentially compromising the accuracy of the clusters. To address this issue, a novel structural graph clustering algorithm based on the adaptive selection of density peaks is proposed in this paper. Unlike traditional methods, our algorithm does not rely on external parameters and eliminates the need for manual selection of density peaks or cluster centers by users. Density peaks are adaptively identified using the generalized extreme value distribution, with consideration of the structural similarities and interdependencies among nodes, and clusters are expanded by incorporating neighboring nodes, enhancing the robustness of the clustering process. Additionally, a distance-based structural similarity method is proposed to re-cluster noise nodes to the correct clusters. Extensive experiments on real and synthetic graph datasets validate the effectiveness of our algorithm. The experiment results show that the ADPSCAN has a superior performance compared with several state-of-the-art (SOTA) graph clustering methods.

Acoustic optimization of a tee via a Helmholtz resonant cavity and noise prediction via a genetic algorithm coupled with the grey model

As a key local component in heating, ventilation and air conditioning (HVAC) systems, the acoustic characteristics of the tee largely determine the indoor acoustic environment quality. The aim of this study was to determine the impact of the Helmholtz resonant cavity (HRC) on the tee noise and sound transmission loss (STL). The noise was predicted using the Ffowcs Williams-Hawkings (FW-H) equation and large eddy simulation (LES), and an analysis was conducted on four design variables: the cavity width, cavity height, outlet flow ratio, and hole width. The results indicated that increasing the hole width had a positive effect on reducing the noise of the tee. HRC could result in a tee peak noise attenuation up to 34.81 dB. In addition, based on grey model (GM) and genetic algorithm (GA) theory, the noise of the Helmholtz resonant tee (HRT) was predicted, and a noise prediction formula for resonant cavity structure paraments was derived. This study provides a new perspective for optimizing the STL of the tee and a simplified prediction method for low-noise tee design.

Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined. To determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI. The portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity. The SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance (P < 0.001) and lesion conspicuity (P = 0.010). DLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H.

Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT

BackgroundTo assess the improvement of image quality and diagnostic acceptance of thinner slice iodine maps enabled by deep learning image reconstruction (DLIR) in abdominal dual-energy CT (DECT).MethodsThis study prospectively included 104 participants with 136 lesions. Four series of iodine maps were generated based on portal-venous scans of contrast-enhanced abdominal DECT: 5-mm and 1.25-mm using adaptive statistical iterative reconstruction-V (Asir-V) with 50% blending (AV-50), and 1.25-mm using DLIR with medium (DLIR-M), and high strength (DLIR-H). The iodine concentrations (IC) and their standard deviations of nine anatomical sites were measured, and the corresponding coefficient of variations (CV) were calculated. Noise-power-spectrum (NPS) and edge-rise-slope (ERS) were measured. Five radiologists rated image quality in terms of image noise, contrast, sharpness, texture, and small structure visibility, and evaluated overall diagnostic acceptability of images and lesion conspicuity.ResultsThe four reconstructions maintained the IC values unchanged in nine anatomical sites (all p > 0.999). Compared to 1.25-mm AV-50, 1.25-mm DLIR-M and DLIR-H significantly reduced CV values (all p < 0.001) and presented lower noise and noise peak (both p < 0.001). Compared to 5-mm AV-50, 1.25-mm images had higher ERS (all p < 0.001). The difference of the peak and average spatial frequency among the four reconstructions was relatively small but statistically significant (both p < 0.001). The 1.25-mm DLIR-M images were rated higher than the 5-mm and 1.25-mm AV-50 images for diagnostic acceptability and lesion conspicuity (all P < 0.001).ConclusionsDLIR may facilitate the thinner slice thickness iodine maps in abdominal DECT for improvement of image quality, diagnostic acceptability, and lesion conspicuity.

Spatial domain noise removal filtering for low-resolution digital images

&lt;p&gt;n this research work, six different filters are applied on a low resolution 8 b/pixel gray-scale images, which operate on small sub-images (windows of 3×3 to 11×11 pixels). The enhanced images are used to compare the efficiency of the different six filters using the peak signal to noise ratio (PSNR) image quality measure. Noise peak elimination filter (PSNR)=36.63) outperforms others, such as median filter (PSNR=36.61), while corruption estimation (PSNR=36.03) significantly cuts processing time by only processing the corrupted pixels while maintaining image details. Mean filter (PSNR=34.05) is sensitive to outliers, which cause the image's sharpness and fine features to be lost. By avoiding averaging across edges, bimodal-averaging filter (PSNR=35.30), which improves on the mean filter, chooses the mean of the biggest population. The median-mean filtering (PSNR=36.32), which combines median and mean filters and determines the output pixel by averaging the median and some nearby pixels, is another improvement above averaging.&lt;/p&gt;

Perceptual thresholds for differences in CT noise texture.

The average () or peak () noise power spectrum (NPS) frequency is often used as a one-parameter descriptor of the CT noise texture. Our study develops a more complete two-parameter model of the CT NPS and investigates the sensitivity of human observers to changes in it. A model of CT NPS was created based on its and a half-Gaussian fit () to the downslope. Two-alternative forced-choice staircase studies were used to determine perceptual thresholds for noise texture, defined as parameter differences with a predetermined level of discrimination performance (80% correct). Five imaging scientist observers performed the forced-choice studies for eight directions in the -space, for two reference NPSs (corresponding to body and lung kernels). The experiment was repeated with 32 radiologists, each evaluating a single direction in the -space. NPS differences were quantified by the noise texture contrast (), the integral of the absolute NPS difference. The two-parameter NPS model was found to be a good representation of various clinical CT reconstructions. Perception thresholds for alone are for body and for lung NPSs. For , these values are 0.15 and , respectively. Thresholds change if the other parameter also changes. Different NPSs with the same or can be discriminated. Nonradiologist observers did not need more than radiologists. or is insufficient to describe noise texture completely. The discrimination of noise texture changes depending on its frequency content. Radiologists do not discriminate noise texture changes better than nonradiologists.