Directional Transfer Functions Research Articles

Optical directional differential operation enabled visual chirality detection.

Directional differential operation can extract the changes of directional information from complex signals, and plays an important role in target recognition and texture image processing. Here, we propose an optical directional differential operation based on large cross-polarization rotation, and realize the visual detection of chiral enantiomers. By using cross-polarization rotation in a specified direction, we design a corresponding directional spatial spectral transfer function whose transmission efficiency increases as the incident angle approaches the Brewster angle. The differential direction can be adjusted by changing the initial polarization state, and can be used to detect the concentration of chiral solutions. Finally, we apply the directional differential operation to achieve the visual detection of chiral enantiomers.

Effects of indoor exposure to low level toluene on neural network alterations during working memory encoding

ObjectiveWhile high concentrations of toluene are known to affect multiple human organ systems, research concerning the influence of immediate, short-term exposure to toluene indoors and at low concentrations is scarce. Here, we studied effects of indoor toluene exposure on neural network alterations during working memory (WM) encoding. MethodsA total of 23 healthy college students were recruited. All participants were situated in a closed environmental chamber with a full fresh air system. Each participant was subjected to four exposure experiments with different toluene concentrations (0, 17.5, 35, and 70 ppb, named Group A, B, C and D, respectively), with at least one week between each experiment. WM Behavioral and 19-channel electroencephalogram (EEG) recordings in a pre-set environmental chamber were conducted simultaneously during each toluene exposure experiment. Neural networks relevant to WM encoding were visualized analyzing the obtained data. Results1. No significant difference in WM behavioral performance among the four groups was found. However, a significant increase in whole brain neural network functional connectivity was noted, especially in the frontal region.2. An outflow directional transfer function (DTFoutflow) revealed higher frontal region values among Group D (the 70 ppb group) as compared to Group A, B and C (the0, 17.5 ppb and 35 ppb groups, respectively), although no differences in frontal region DTFinflow values among the four groups were noted.3. The DTFFZ-F7, DTFFZ-T5, DTFFZ-P4, DTFFZ-P3, DTFFP2-O2, DTFP3-T4, DTFP3-F4, DTFP4-CZ and DTFP4-T4 values of Group D were found to be higher as compared to those of Group A and B. Furthermore, DTFFZ-F7 and DTFP4-T4 values of Group C were higher as compared to those of Group A. The DTFFZ-F7 values of Group D were higher as compared to those of the Group C. ConclusionShort-term toluene exposure significantly influences neural networks during cognitive processes such as WM encoding, even at low concentration.

Dynamic analysis of epileptic causal brain networks based on directional transfer function

Epilepsy is a neurological disease with disordered brain network connectivity. It is important to analyze the brain network mechanism of epileptic seizure from the perspective of directed functional connectivity. In this paper, causal brain networks were constructed for different sub-bands of epileptic electroencephalogram (EEG) signals in interictal, preictal and ictal phases by directional transfer function method, and the information transmission pathway and dynamic change process of brain network under different conditions were analyzed. Finally, the dynamic changes of characteristic attributes of brain networks with different rhythms were analyzed. The results show that the topology of brain network changes from stochastic network to rule network during the three stage and the node connections of the whole brain network show a trend of gradual decline. The number of pathway connections between internal nodes of frontal, temporal and occipital regions increase. There are a lot of hub nodes with information outflow in the lesion region. The global efficiency in ictal stage of α, β and γ waves are significantly higher than in the interictal and the preictal stage. The clustering coefficients in preictal stage are higher than in the ictal stage and the clustering coefficients in ictal stage are higher than in the interictal stage. The clustering coefficients of frontal, temporal and parietal lobes are significantly increased. The results of this study indicate that the topological structure and characteristic properties of epileptic causal brain network can reflect the dynamic process of epileptic seizures. In the future, this study has important research value in the localization of epileptic focus and prediction of epileptic seizure.

Alertness Estimation Using Connection Parameters of the Brain Network

Alertness mechanism of unmanned monitoring vehicles to environment is important. Especially, the vigilance modeling of underground security robots has a particularly significance because the underground is a dangerous environment. However, there is no a mature methodology for the alertness computation. In this work, four parts of the alertness estimation are focused. First, an autonomous robot alertness mechanism framework is proposed by using the deep reinforcement learning model of the human alertness mechanism. Second, a fast K-T filtering algorithm is developed to eliminate the multiple noises of the electroencephalograph (EEG) signals by the blind source separation and the adjustable <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> factor wavelet transform. Third, the description problem of the directed interaction stability of the cortical EEG signals is solved by the ensemble empirical mode decomposition and the directional transfer function. Fourth, the human alertness estimation is explored by using the support vector regression of the dynamically spatial-temporal brain network connection parameters. Experiments show that, the mean square error and the determination coefficient of the explored alertness estimation are respectively 0.115 and 0.8337. Compared with the scalp EEG alertness estimation, it has a better performance because the mean square error is decreased by 0.0684, and the determination coefficient is increased by 0.023.

Time-frequency and Network Analysis of Hippocampus in APP/PS1 Double Transgenic Mice with Dementia of Different Degrees

Hippocampal atrophy and neuron loss are common symptoms of Alzheimer's disease (AD). The hippocampal region is well known for producing oscillations at different frequency bands due to the neuronal network architecture. However, the mechanism of Ripple high frequency variation in hippocampal region with the course of AD disease has not been correctly assessed. We proposed time-frequency analysis using wavelet transform and constructing Granger causality network to analyze the characteristics of Hippocampal sharp wave-ripple (SPW-R) complexes in APP/PS1 mice at different cognitive levels. We use wavelet transform to overcome the shortcoming that the traditional Short Time Fourier Transform cannot deal with the unsteady signal frequency, and construct the Granger causality network to verify our results. By analyzing ripple frequency band energy changes and directional transfer function matrix in hippocampal CA1 region of mice with different cognitive levels, we found that the loss of ripple high frequency energy and decreased network connectivity in hippocampal CA1 region of APP/PS1 mice were correlated with the degree of memory loss. We believe that from mild dementia to severe dementia. The decreased cell activity in APP/PS1 mouse CA1 region leads to changes in Ripple high-frequency time-frequency energy and network connectivity for theoretical reasons. Our results provide support for assessing cognitive loss in APP/PS1 mice from the perspective of Ripple high frequency in hippocampus CA1 region.

Anisotropic solid-state PLA foaming templated by crystal phase pre-oriented with 3D printing: cell supporting structures with directional capillary transfer function.

Bones represent a superb biomaterial that combines high mechanical stiffness with nutrition delivery to its osteocyte cells through the microscopical Haversian canals and bone canaliculi. Such a structure is hard to reproduce artificially, though. 3D printing delivers an unprecedented shape control of the created objects. Yet the resolution limit of the most common 3D printers is insufficient, lying between tens to hundreds of microns, while more precise 3D printing techniques fail in fabricating larger objects. We present a unique, yet simple and versatile method for preparing hierarchically aligned microporous canals using a biocompatible polymer polylactic acid (PLA) with their structure controlled at the submicron to macro scale. The layout was inspired by the microscopical Haversian canals and bone canaliculi of cortical bone. This procedure takes advantage of the PLA complex crystalline behavior, which was pre-oriented by 3D printing, orientedly crystallized in CO2, foamed, and cryo-shrunk. The canal formation was assessed via WAXS, FTIR spectroscopy, and DSC and complemented by the evaluation of mechanical properties, biocompatibility, and directionally selective capillary transport in the final structure. The fine dimensions of the canals unmatched by the common 3D printing techniques capable of making macroscale objects combined with the abovementioned properties represent promising potential for various applications, such as advanced cell-supporting designs with a built-in nutrition function.

Sensitivity analysis of pinna morphology on head-related transfer functions simulated via a parametric pinna model.

The head-related transfer function (HRTF) defines the acoustic path from a source to the two ears of a listener in a manner that is highly dependent on direction. This directional dependence arises from the highly individual morphology of the pinna, which results in complex reflections and resonances. While this notion is generally accepted, there has been little research on the importance of different structural elements of the pinna on the HRTF. A parametric three-dimensional ear model was used to investigate the changes in shape of the pinna in a systematic manner with a view to determining important contributing morphological parameters that can be used for HRTF individualization. HRTFs were simulated using the boundary element method. The analysis comprised objective comparisons between the directional transfer function and diffuse field component. The mean spectral distortion was used for global evaluation of HRTF similarity across all simulated positions. A perceptual localization model was used to determine correspondences between perceptual cues and objective parameters. A reasonable match was found between the modelled perceptual results and the mean spectral distortion. Modifications to the shape of the concha were found to have an important impact on the HRTF, as did those in proximity to the triangular fossa. Furthermore, parameters that control the relief of the pinna were found to be at least as important as more frequently cited side-facing parameters, highlighting limitations in previous morphological/HRTF studies.

Three-dimensional pore-scale study of the directional heat transfer in a high thermal conductivity carbon/carbon composite protection system

High-efficiency thermal protection is becoming a critical design criterion for supersonic aircraft. Currently, there is significant research on accurately and efficiently designing heat protection systems, particularly at the high temperature stagnation point region of supersonic aircraft. In this work, a three-dimensional high thermal conductivity carbon/carbon composite thermal protection system with a directional heat transfer function is proposed to realize a high-efficiency thermal protection design in the stagnation point region. A comprehensive method that combines the lattice Boltzmann method (LBM) and finite volume method (FVM) was designed to investigate the heat transfer process in the proposed structure at the pore scale. The FVM was applied to calculate the heat radiative information, which was required to solve the energy equation with the LBM. A failure temperature is defined to quantitatively describe how well the heat transfer occurs in the designed direction in the proposed structure. The effects of the temperature of the stagnation point, thermal conductivity of the carbon fibers, carbon fiber diameters, and position of the carbon fibers on the heat transfer in the proposed structure were studied in detail. The results show that the proposed comprehensive method can predict the heat transfer in the proposed structure accurately. A competitive relationship exists between the directional heat conduction and the radiation heat transfer. The radiation heat transfer became more dominating as the temperature increased. The failure temperature for the directional heat transfer in the proposed structure increased with the thermal conductivity of the carbon fibers and the carbon fiber diameters, while it decreased as the distance between the position of the carbon fibers and the nose of the blunt structure increased. The above phenomena will be helpful for designing high-performance thermal protection systems with carbon/carbon composites.

Electroencephalography and Functional Magnetic Resonance Imaging-Guided Simultaneous Transcranial Direct Current Stimulation and Repetitive Transcranial Magnetic Stimulation in a Patient With Minimally Conscious State.

ObjectiveA minimally conscious state (MCS) is characterized by discernible behavioral evidence of consciousness that cannot be reproduced consistently. This condition is highly challenging to treat. Recent studies have demonstrated the potential therapeutic effect of non-invasive brain stimulation in patients with MCS. In one patient in an MCS, we delivered simultaneous transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) based on an individual brain network analysis and evaluated the therapeutic effect.MethodsThe directional transfer function (DTF) was calculated based on electroencephalograph (EEG) analysis. Global brain connectivity was calculated based on functional magnetic resonance imaging (fMRI) analysis. By referring to the EEG and fMRI results, we identified inferior parietal lobes (IPLs) as targets. In the 2-week treatment period, 14 sessions were applied to the identified bilateral parietal regions. Simultaneous 1.5-mA anodal tDCS and 5-Hz rTMS were delivered for 20 min per hemisphere in each session. Clinical evaluation scores were recorded weekly throughout the treatment. A second patient given the routine treatment was evaluated as a control.ResultsThe clinical scores of patient 1 with MCS improved after 2 weeks of stimulation treatment, and the effect lasted for up to 1 month. EEG analysis showed a significant increase (p < 0.001) in the DTF value in the gamma band in a bilateral set of posterior regions, and fMRI showed a trend toward normalized activity in the IPLs. The clinical scores of patient 2 with coma did not improve much after 2 weeks of routine treatment. The EEG analysis showed a significant increase (p = 0.021) in the DTF value in the gamma band in a bilateral set of posterior regions.ConclusionThe application of EEG and fMRI to characterize the functional connectivity features of the network in an MCS patient provided a reasonable and accurate stimulation target and verified the changes in functional connectivity resulting from stimulation.

Directional Equalization of Sparse Head-Related Transfer Function Sets for Spatial Upsampling

Acquiring decent full-spherical sets of head-related transfer functions HRTFs based on a small number of measurements is highly desirable. For spatial upsampling, HRTF interpolation in the spatially continuous spherical harmonics SH domain is a common approach. However, the number of measured HRTFs limits the assessable SH order, resulting in order-limited HRTFs when transformed to the SH domain. Thus, the SH representation of sparse HRTF sets shows restricted spatial resolution and suffers from order-limitation errors. We present a method that reduces these errors by a directional equalization prior to the SH transform. This is done by a spectral division of each HRTF with a corresponding directional rigid sphere transfer function. The processing removes direction-dependent temporal and spectral components and, therefore, significantly reduces the spatial complexity of the HRTF set, allowing for an enhanced interpolation of HRTFs at reduced SH orders. Spatial upsampling is achieved by an inverse SH transform on an arbitrary dense sampling grid. A subsequent de-equalization by a spectral multiplication with the rigid sphere transfer function recovers the energy in higher spatial orders that was not inherent in the sparse HRTF set. For evaluation, HRTFs were calculated for various limited orders from sparse datasets and compared to a reference. The results show that the proposed method clearly outperforms common SH interpolation of HRTF spectra regarding the overall spectral and temporal structure as well as modeled localization performance.

Development of the head, pinnae, and acoustical cues to sound location in a precocial species, the guinea pig (Cavia porcellus)

The morphology of the head and pinna shape the spatial and frequency dependence of sound propagation that give rise to the acoustic cues to sound source location. During early development, the physical dimensions of the head and pinna increase rapidly. Thus, the binaural (interaural time and level differences, ITD and ILD) and monaural (spectral shape) cues are also hypothesized to change rapidly. Complex interactions between the size and shape of the head and pinna limit the accuracy of simple acoustical models (e.g. spherical) and necessitate empirical measurements. Here, we measured the cues to location in the developing guinea pig, a precocial species commonly used for studies of the auditory system. We measured directional transfer functions (DTFs) and the dimensions of the head and pinna in guinea pigs from birth (P0) through adulthood. Dimensions of the head and pinna increased by 87% and 48%, respectively, reaching adult values by ∼8 weeks (P56). The monaural acoustic gain produced by the head and pinna increased with frequency and age, with maximum gains at higher frequencies (>8 kHz) reaching values of 10–21 dB for all ages. The center frequency of monaural spectral notches also decreased with age, from higher frequencies (∼17 kHz) at P0 to lower frequencies (∼12 kHz) in adults. In all animals, ILDs and ITDs were dependent on both frequency and spatial location. Over development, the maximum ILD magnitude increased from ∼15 dB at P0 to ∼30 dB in adults (at frequencies >8 kHz), while the maximum low frequency ITDs increased from ∼185 μs at P0 to ∼300 μs in adults. These results demonstrate that the changes in the acoustical cues are directly related to changes in head and pinna morphology.

Inverse filtering approach to measure directional in-plane modulation transfer function using a sphere phantom for a digital tomosynthesis system.

We propose a method to measure the directional in-plane modulation transfer function (MTF) of a digital tomosynthesis system using a sphere phantom. To assess the spatial resolution of an in-plane image of the tomosynthesis system, projection data of a sphere phantom were generated within a limited data acquisition range of 40°, and reconstructed by the FDK algorithm. To measure the in-plane MTF, we divided the Fourier transform of the reconstructed sphere phantom by that of the ideal sphere phantom, and then performed plane integral along the fz-direction. When dividing, small values in the denominator can introduce estimation errors, and these errors were reduced by the proposed method. To evaluate the performance of the proposed method, the in-plane MTF estimated by simulation and experimental data was compared to the ideal in-plane MTF generated by computer simulations using a point object. For quantitative evaluation, we measured frequency values at half-maximum and full-maximum of the directional in-plane MTF along the three different directions (i.e., f0° -, f30° -, and f60° -directions) and compared them with those of the ideal in-plane MTF. Although the sphere phantom has been regarded as an inappropriate object due to the anisotropic characteristics of tomosynthesis image, our results show that the proposed method has a reliable estimation performance, demonstrating the sphere phantom is still suitable for measuring the directional in-plane MTF for a digital tomosynthesis system.

Improved understanding of head-related transfer functions through sagittal-plane spectral decomposition

Head-related transfer functions (HRTFs) capture the listener-specific modifications that are imparted on a sound as it travels from a specific location in space, interacts with the listener’s head, shoulders, and outer ears, and arrives at the ear drums. HRTFs have often been decomposed into a combination of two parts to aid modeling and analysis: a diffuse-field transfer function (DFTF) that captures non-directional but still listener-specific spectral details of the HRTF, and a directional transfer function (DTF) that captures all of the listener-specific directional information. Because the DTF contains spectral variation along all spatial dimensions, it does not provide a way to separate the spectral cues responsible for lateral and sagittal plane localization judgments, which are largely independent. As an alternative approach, decomposing an HRTF along each sagittal plane (aka along the “cones-of-confusion”) provides similar benefits to DTF analysis while providing additional insights into the spectral cues responsible for lateral and vertical localization, independently. This talk will provide a detailed overview of sagittal-plane spectral decomposition along with experimental results showing how the technique can be applied to improve localization with non-individualized HRTFs, separate general and idiosyncratic HRTF features, and cluster listeners’ HRTFs based on spectral similarity.

Sound localization performance with level-dependent hearing protection devices

Level-dependent hearing protection devices (HPDs) offer the promise of the ability to hear low-level sounds while providing protection against dangerous high-level sounds. These devices are useful for people who may be exposed to intermittent, unexpected loud sounds while operating in environments that are otherwise generally quiet. Often, it is important for these users to be able to localize sounds and to maintain auditory situation awareness in these environments while wearing the HPDs. Measurements were made of listeners’ abilities to localize quiet and loud sound sources while wearing different level-dependent devices, as well as with unprotected ears. Electroacoustic measurements were also made with the devices on an acoustic test fixture to characterize their input-output functions, effective bandwidths, and directional transfer functions. Sound localization performance was typically worse when wearing the HPDs than with unprotected ears, with more front/back confusions, especially for the devices ...

The use of auditory models for the prediction of protected-ear localization

Several authors have shown that listeners’ natural auditory localization performance is degraded significantly when wearing a hearing protection device (HPD) (Atherley and Noble, 1970; Abel and Armstrong, 1993; Bolia et al., 2001; Brungart et al., 2007; Hobbs et al.,2008). Research suggests that this degradation in protected-ear localization caused by the disruption of the natural spatial hearing cues by physical obstructions such as a plug or muff, as well as active systems’ artifacts like a limited frequency response, temporal processing delay, or artificial directionality. The current work investigated the utility of using existing auditory localization models from The Auditory Modelling Toolbox (Sondergaard and Majdak (2013)), along with measurements of the device directional transfer function, to accurately predict behavioral protected-ear localization performance. Ten listeners were asked to localize 250-ms broadband noise bursts originating from 245 spatial locations surrounding the listener while wearing each of 11 different HPDs (a mixture of active and passive, plugs and muffs). Directional transfer functions were also collected for each subject, device, and location. Results indicate good agreement between observed behavioral results and model predictions when viewed macroscopically (global mean error values), but less agreement was seen on a trial-by-trial basis.

Temporary unilateral hearing loss during development impairs behavioral and neural sensitivity to interaural level difference cues for sound localization

Children who experience persistent conductive hearing loss (CHL) early in life often display binaural hearing impairments that persist long after CHL is resolved, suggesting abnormal central auditory development. Abnormal sensitivity to interaural level differences (ILDs) is particularly likely as a CHL (such as an ear infection) can attenuate sound in the affected ear by >30 dB, dramatically distorting ILD cues. Here, we quantified the effects of unilateral CHL on (1) behavioral spatial acuity and (2) neural information processing of ILD cues in the guinea pig auditory midbrain (inferior colliculus, IC) using the mathematical framework of Fisher information (FI). Animals raised with unilateral CHL displayed larger minimum audible angles for high-pass noise compared to age-matched controls, suggesting impaired ILD sensitivity. Based on acoustic directional transfer function measurements, ILD discrimination thresholds were elevated by ~3–6 dB. Following behavior, extracellular recordings were made in the I...

A Sphere Phantom Approach to Measure Directional Modulation Transfer Functions for Tomosynthesis Imaging Systems.

We propose a sphere phantom approach to measure spatially varying directional modulation transfer functions (MTFs) for tomosynthesis imaging systems. Since the reconstructed tomosynthesis images contain significant artifacts, traditional background detrending techniques may not be effective to estimate the background trends accurately, which is essential to acquire sphere only data. A background detrending technique optimized for local volumes with different cone angles is presented. To measure directional MTFs, we calculate plane integrals of ideal sphere phantom and sphere only data. To minimize the effects of the high level of noise in tomosynthesis images, Richardson-Lucy deconvolution with Tikhonov-Miller is used to estimate directional plane spread function (PlSF). Then, directional MTFs are calculated by taking the modulus of the Fourier transform of the directional PlSFs. The measured directional MTFs are compared with the ideal directional MTFs calculated from a simulated point object. Our results show that the proposed method reliably measures directional MTFs along any desired directions, especially near low frequency regions.

Effects of active and passive hearing protective devices on sound source localization, tone detection, and speech recognition

Hearing protective devices (HPDs) such as earplugs and earmuffs offer to mitigate noise exposure and thus noise-induced hearing loss among persons frequently exposed to intense sound, e.g., military personnel or industrial workers. However, distortions of spatial acoustic information and attenuation of low-intensity sounds caused by many existing HPDs can make their use untenable in high-risk environments where auditory situational awareness is imperative. Here, we assessed (1) sound source localization accuracy using a head-turning paradigm, (2) tone detection thresholds using a two-alternative forced-choice task, and (3) speech-in-noise recognition using a modified version of the QuickSIN test in 10 young normal-hearing males wearing four different HPDs (two active, two passive), including two new and previously untested devices. Relative to unoccluded (control) performance, all tested HPDs significantly degraded performance across tasks, although one active HPD slightly improved high-frequency tone detection thresholds, and did not degrade speech recognition. Behavioral data were examined with respect to binaural acoustic information (directional transfer functions) measured in a binaural manikin with and without tested HPDs. Data reinforce previous reports that HPDs significantly compromise auditory perceptual facilities, particularly sound localization due to distortions of high-frequency pinna cues.

Linear coding of complex sound spectra by discharge rate in neurons of the medial nucleus of the trapezoid body (MNTB) and its inputs

The interaural level difference (ILD) cue to sound location is first encoded in the lateral superior olive (LSO). ILD sensitivity results because the LSO receives excitatory input from the ipsilateral cochlear nucleus and inhibitory input indirectly from the contralateral cochlear nucleus via glycinergic neurons of the ipsilateral medial nucleus of the trapezoid body (MNTB). It is hypothesized that in order for LSO neurons to encode ILDs, the sound spectra at both ears must be accurately encoded via spike rate by their afferents. This spectral-coding hypothesis has not been directly tested in MNTB, likely because MNTB neurons have been mostly described and studied recently in regards to their abilities to encode temporal aspects of sounds, not spectral. Here, we test the hypothesis that MNTB neurons and their inputs from the cochlear nucleus and auditory nerve code sound spectra via discharge rate. The Random Spectral Shape (RSS) method was used to estimate how the levels of 100-ms duration spectrally stationary stimuli were weighted, both linearly and non-linearly, across a wide band of frequencies. In general, MNTB neurons, and their globular bushy cell inputs, were found to be well-modeled by a linear weighting of spectra demonstrating that the pathways through the MNTB can accurately encode sound spectra including those resulting from the acoustical cues to sound location provided by head-related directional transfer functions (DTFs). Together with the anatomical and biophysical specializations for timing in the MNTB-LSO complex, these mechanisms may allow ILDs to be computed for complex stimuli with rapid spectrotemporally-modulated envelopes such as speech and animal vocalizations and moving sound sources.

A new method to measure directional modulation transfer function using sphere phantoms in a cone beam computed tomography system.

We propose a new method to measure directional modulation transfer function (MTF) using sphere phantoms in a cone beam computed tomography (CBCT) system. To measure spatially varying 3-D MTFs, we model FDK reconstruction in local regions and calculate the plane integrals of an ideal sphere phantom and reconstructed sphere phantoms. Then, we modify the Richardson-Lucy (RL) deconvolution method to relax the non-negativity constraint in RL deconvolution and apply it to estimate the directional plane spread functions (PlSFs). Directional MTFs are calculated by taking the modulus of the Fourier transform of the estimated directional PlSFs. To validate the proposed method, we simulate ideal 3-D MTFs and compare them with directional MTFs measured by simulation and experimental data along three major axes. For quantitative evaluation, we compare full-width at half-maximum (FWHM) and full-width at tenth-maximum (FWTM) of measured and ideal directional MTFs. The measured directional MTFs from simulation and experimental data show excellent agreement with the ideal directional MTFs, demonstrating the effectiveness of the proposed method to estimate directional MTFs in a CBCT system.