Reconstruction Filter Research Articles

Automated Framework for Segmenting Skin Lesions using Artificial Bee Colony Optimization with Morphological Reconstruction

Nowadays, Many people are affected by skin cancers. Our proposed work designed a framework to extract the skin cancer using artificial bee colony with morphological reconstruction filters, which helps the demonologist to prevent the severity in early stage, Melanoma is the now become a harmful form of skin cancer which leads the skin cells to grow rapidly and form cancerous tumors. We collected various melanoma images from having used samples from public dataset like ISIC archive and a few from clinical datasets. To remove the noise, median filtering is used for preprocessing in the first step, to segment the tumor boundary Artificial bee colony is used and to remove the unwanted pixels using morphological reconstruction filters. Segmentation metrics like precision, recall, accuracy, Mean Square Error, Peak signal to noise ratio and computational time were calculated. Our proposed method yield 97.7% segmentation accuracy when compared with the level set method and Fuzzy C Means clustering techniques

Generalized Sampling on Graphs With Subspace and Smoothness Priors

We propose a framework for generalized sampling of graph signals that parallels sampling in shift-invariant (SI) subspaces. This framework allows for arbitrary input signals, which are not constrained to be bandlimited. Furthermore, the sampling and reconstruction filters may be different. We present design methods of the correction filter that compensate for these differences and lead to closed form expressions in the graph frequency domain. In this study, we consider two priors on graph signals: The first is a subspace prior, where the signal is assumed to lie in a periodic graph spectrum (PGS) subspace. The PGS subspace is proposed as a counterpart of the SI subspace used in standard sampling theory. The second is a smoothness prior that imposes a smoothness requirement on the graph signal. We suggest the use of recovery techniques for when the recovery filter can be optimized and under a setting in which a predefined filter must be used. Sampling is performed in the graph frequency domain, which is a counterpart of "sampling by modulation" used in SI subspaces. We compare our approach with existing sampling techniques on graph signal processing. The effectiveness of the proposed generalized sampling approach is validated numerically through several experiments.

Data compression in ViSAR sensor networks using non-linear adaptive weighting

Nowadays, industrial video synthetic aperture radars (ViSARs) are widely used for aerial remote sensing and surveillance systems in smart cities. A main challenge of a group of networked ViSAR sensors in an IoT-based environment is low bandwidth of wireless links for communicating big video data. In this research, we propose a non-linear statistical estimator for adaptive reconstruction of compressed ViSAR data. Our proposed reconstruction filter is based on an adaptively generated non-linear weight mask of spatial observations. It can strongly outperform several conventional and well-known reconstruction filters for three different video samples.

An Improved Watershed Segmentation Algorithm of Medical Tumor Image

Aiming at the problem that the tumor is difficult to be accurately segmented due to noise and edge discontinuity in the chest breast MRI image, a medical image segmentation algorithm based on gradient edge detection and control marked watershed is proposed. Firstly, the mathematical morphology reconstruction filter is used to remove the small texture and noise of the MRI image of the breast tumor, and then the local minimum associated with the object is extracted from the low-frequency components of the gradient image, and they are formed into a binary marker image; The reconstructive technique is forced to be the local minimum of the original gradient image, the adaptive correction of the gradient image is realized, and finally the watershed segmentation is performed. The experimental results show that the algorithm can automatically and quickly extract the breast tumor region in the series of MRI images and realize the automatic segmentation of the region of interest in the medical image.

Method to calculate frequency characteristics of reconstruction filter kernel in X-ray computed tomography.

A computed tomography (CT) image is generally reconstructed by a filtered back projection (FBP) algorithm. In an FBP algorithm, the image quality primarily depends on a reconstruction filter kernel. Although the details of the filter kernel are not disclosed to users, the frequency response of the filter kernel can theoretically be calculated using the relational formula of the filter kernel and the modulation transfer function (MTF) of the reconstruction algorithm (MTFA). In this study, we proposed a method to determine the frequency response of a filter kernel and verify its validity. Two clinical CT scanners were used to derive the filter kernel. The MTF was obtained and subsequently separated to the MTF of the scanner system and MTFA. Using the relational formula of the filter kernel and MTFA, we calculated the frequency response of the filter kernel. To verify the calculated result, we measured the noise power spectrum (NPS). Additionally, the filter kernel was calculated using the relational formula of the filter kernel and NPS. In both CT scanners, the filter kernels calculated by the two methods showed good agreement, and we confirmed the validity of the results and the effectiveness of the proposed method. Furthermore, the inherent image quality performance of the CT scanner could be clarified by the reconstruction filter kernel.

On the Signal Filtering Property of CT Incremental Sigma–Delta ADCs

In this brief, the calculation of the signal behavior and the achievable signal-to-quantization-noise ratio of continuous-time (CT) incremental sigma–delta (I-SD) analog-to-digital converters (ADCs) is described. The presented method allows for the analysis of I-SD ADCs in frequency domain, including the specific non-idealities of the CT modulator. In the state-of-the-art, it is described that the omission of the preceding sample-and-hold for the I-SD ADC alters the transfer characteristic compared to a Nyquist-rate converter. So far, for CT I-SD ADCs this behavior is only investigated via simulations. In this brief, the model of a discrete-time I-SD ADC is generalized and adapted for the CT case. This allows to analytically obtain the signal and noise transfer function of the I-SD ADC in frequency domain in combination with arbitrary reconstruction filters due to the utilization of the lifting method in a fast and accurate way.

Systolic array design space exploration of interpolators for multi‐rate systems

This study presents the development and comparison of interpolator systolic array designs and implementations. Systematic methodology was applied to the difference equations defining the interpolator algorithm. A dependence graph for the interpolator was obtained that combined the upsampler and the anti-imaging filter. Different data scheduling and projection operations were developed. Nine systolic array design options were obtained and evaluated. The fastest design was selected for hardware implementation. Field-programmable gate array implementations for the conventional and proposed designs confirm that the proposed interpolator implementation requires no more than 61.7% of the hardware resources required in the conventional design and are at least 63.9% faster than the conventional design.

A Simultaneous Imaging Scheme of Stationary Clutter and Moving Targets for Maritime Scenarios with the First Chinese Dual-Channel Spaceborne SAR Sensor

The technique of azimuth multichannel synthetic aperture radar (SAR) system has become a potential solution to the irreconcilable conflict between high-resolution and wide-swath (HRWS) confronted with in a traditional SAR system. Unambiguous imaging, especially for a scene with moving targets, is one of the crucial research topics in the HRWS SAR system. This paper proposes a simultaneous imaging scheme of moving targets and stationary clutter for maritime scenarios. First, the moving target echoes are extracted from the stationary clutter. After that, two methods working in completely different principles are used to estimate the radial velocity of each moving target, and the estimated result is used for phase compensation. After that, the moving target echoes are added back to the stationary scene echo and sent to the reconstruction filter. Lastly, the reconstructed echo can be processed by the classical Chirp Scaling (CS) algorithm. Experiments are carried out using the Chinese GaoFen-3 dual-channel data. The estimated velocities of the moving targets are verified by automatic identification service (AIS) information, and the imaging results show that the false targets are effectively suppressed and the moving targets also return to their correct positions along the azimuth.

Imaging dynamic scenes with a spatio-temporally channeled polarimeter.

Most channeled polarimeters modulate the intensity in a single independent domain such as space, time, or wavenumber. Recently we proposed and modeled a concept for a system modulated simultaneously in space and time [Opt. Lett.43, 2768 - 2771 (2018)] and demonstrated that superior performance could be obtained by trading off spatial and temporal bandwidth in the system. Here we present results from a prototype realization of such a system and demonstrate quantitatively that the spatial modulation transfer function of the imager can be improved by choosing the appropriate modulation strategy for a given scene spatial and temporal bandwidth. We demonstrate that a hybrid modulation system can achieve the high spatial frequency performance of a time modulated system for static scenes, or it can achieve the high temporal frequency performance of a spatially modulated system for rapidly varying scenes, and it can out perform both systems for scenes with intermediate bandwidth in both domains. Moreover, the physical system implementation is essentially the same for each system type, which in principle allows the reconstruction strategy to be selected in real-time by choosing the appropriate reconstruction filters.

Review of Channel Estimation for Candidate Waveforms of Next Generation Networks

The advancement in wireless communication applications encourages the use of effective and efficient channel estimation (CE) techniques because of the varying behaviour of the Rayleigh fading channel. In most cases, the emphasis of most proposed CE schemes is to improve the CE performance and complexity for ensuring quality signal reception and improved system throughput. Candidate waveforms whose designs are based on filter bank multi-carrier (FBMC) modulation techniques such as filter bank orthogonal frequency division multiplexing based on offset quadrature amplitude modulation (OFDM-OQAM), universal filtered multicarrier (UFMC) and generalised frequency division multiplexing based on offset quadrature amplitude modulation (GFDM-OQAM) are no exception to the use of these proposed CE techniques in the literature. These schemes are considered as potential waveform candidates for the physical/media access control layer of the emerging fifth generation (5G) networks. Therefore, pinpoint CE techniques represent an important requirement for these waveforms to attain their full potentials. In this regard, this paper reviews the concept of CE as applicable to these waveforms as well as other waveform candidates under consideration in the emerging 5G networks. Since the design of the majority of the waveform candidates is filter based, a review of the general filter design considerations is presented in this paper. Secondly, we review general CE techniques for candidate waveforms of next generation networks and classify some of the studied CE techniques. In particular, we classify the CE schemes used in filter bank OFDM-OQAM and GFDM-OQAM based transceivers and present a performance comparison of some of these CE schemes. Besides, the paper reviews the performances of two linear CE schemes and three adaptive based CE schemes for two FBMC based waveform candidates assuming near perfect reconstruction (NPR) and non-perfect reconstruction (Non-PR) filter designs over slow and fast frequency selective Rayleigh fading channels. The results obtained are documented through computer simulations, where the performances of the studied CE schemes in terms of the normalised mean square error (NMSE) are analysed. Lastly, we summarise the findings of this work and suggest possible research directions in order to improve the potentials of the studied candidate waveforms over Rayleigh fading channels.

Automated MTF measurement in CT images with a simple wire phantom

Abstract This study developed a simple wire phantom and an algorithm to automatically measure the modulation transfer function (MTF) in computed tomography (CT) and implemented it to evaluate the effect of focal spot size and reconstruction filter type. The phantom consisted of a resin cylinder filled with water, with a tin wire of diameter 0.1 mm positioned along the center of the cylinder. The automated MTF algorithm used an axial image of the phantom and comprised several steps. The center position of a region of interest (ROI) was automatically determined at the center of the wire image. The pixels were then summed along the y-direction to obtain the profile of the pixel values at a point along the x-direction. Following this, both edges of the profile were made equal to zero. The profile curve was then normalized so that the total of all the data was equal to unity. The normalized profile curve is the line spread function (LSF), and the MTF curve was obtained by taking its Fourier transform. Our system (phantom and algorithm) is able to differentiate the MTFs of CT images from different focal sizes and reconstruction filter types.

How to CT scan human mummies: Theoretical considerations and examples of use

ObjectiveThe purpose of this study was to develop and provide recommendations for computed tomography (CT) examinations of human mummies. Materials and methodsBased on theoretical considerations and examples, recommendations for use are provided for scanning and image reconstruction parameters. Four examples are presented to illustrate the effect of different CT parameters on image quality. ResultsThe use of appropriate scanning parameters (detector collimation, pitch factor, rotation time) is known to improve image quality; technical considerations favor using lower tube voltage and higher tube current values for the purposes of scanning of human mummies. The use of appropriate image reconstruction parameters (slice thickness, increment, field of view, reconstruction filters) are the basis for individual reconstructions for the purpose of evaluation, documentation, illustration and data storage. ConclusionsDownsizing the field of view to the region of interest as done in the clinical radiological routine represents one major tool to improve image quality. SignificanceThe provided recommendations should improve CT image quality in mummy studies as well as the handling of image data for reconstructions and storage. LimitationsThe recommendations for CT scanning parameters and image reconstructions were written with relatively new generation CT scanners in mind. Only a few examples of use were chosen and image quality assessment was performed subjectively and not by quantitative measurements.

Fast-convolution multicarrier based frequency division multiple access

Fast-convolution multicarrier (FCMC), the asynchronous waveform with ultra-low sidelobe, has appeared to be a promising waveform technique for future wireless communications. In this paper, we investigate the filter bank optimization as well as receiver design including low-complexity channel estimator and equalizer for FCMC based frequency division multiple access (FDMA). Starting from the conventional multi-carrier signals, we first derive a vectorized signal model as a framework to systematically design the FCMC transceiver. For nearly perfect reconstruction (NPR) filter banks design, an optimization criterion which consists of minimizing received signal segments mean square error (MSE) is proposed. From the fact that Toeplitz matrices can be asymptotically diagonalized by discrete Fourier transform (DFT) matrix, the channel equalizer can be simplified to one-tap frequency domain equalizer when DFT size is large enough. The minimum mean square error (MMSE) criterion is then applied to calculate the coefficients of one-tap frequency domain equalizer. In practice, due to the channel fading, the channel estimation has to be performed to obtain the channel state information (CSI) which is required by the channel equalization. To this end, we propose a combined cyclic prefix (CP) and cyclic suffix (CS) pilot structure which facilitates to estimate the frequency domain CSI directly in the receiver end. The proposed FCMC based FDMA features low-complexity receiver, adjustable users bandwidth and low peak-to-average power ratio. Simulation results confirm the performance of the proposed scheme.

Utilization of an optimum low-pass filter during filtered back-projection in the reconstruction of single photon emission computed tomography images of small structures

Introduction:Low-pass filters eliminate noise, and accordingly improve the quality of filtered back-projection (FBP) in the reconstruction of single photon emission computed tomography (SPECT) images. This study aimed at selection of an optimum low-pass filter for FBP reconstruction of SPECT images of small structures. Material and Methods:Spheres A, B, and C (16 mm, 12 mm, and 11 mm in diameter, respectively) attached to capillary stems were filled with technetium-99m solution (activity concentration 300 kBq/mL). They were then mounted inside a Jaszczak Phantom forming a V-shaped structure. The phantom was then filled with distilled water. Two-dimensional (2D) projections were acquired on 128 128 pixels using a Siemens E-Cam dual-head gamma camera. The Parzen, Shepp-Logan, Low Pass Cosine filters (cut-off frequencies: 0.2-0.9), and Butterworth filter (order: 1-9; cut-off frequencies: 0.3-0.9) were employed during FBP reconstruction. The line command of ImageJ software was used to draw the point spread functions of acquired 2D transaxial central slices and for the measurement of their full-width at half-maximum (FWHM). Results:The FWHM of 2D central image slices of spheres A, B, and C reconstructed using a Butterworth filter measured 20, 20, and 10 pixels, respectively. In comparison, the reconstructed images using the Parzen, Low Pass Cosine, and Shepp-Logan filters measured to 27, 25 and, 22 pixels for sphere A, 24, 22, 20 pixels for B, and 22, 20, 18 pixels for C, respectively. Conclusion: The low-pass filters successfully suppressed noise during the FBP reconstruction of SPECT images of small structures. Accordingly, the Butterworth is a suitable choice.

Comparison of Reconstruction Algorithms for F-18 FP CIT PET Images

Fludeoxyglucose-18-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane positron emission tomography (F-18 FP CIT PET) was used for the diagnosis of Parkinson’s disease in nuclear medicine. However, no study of the effect of reconstruction parameters on the quality images obtained using F-18 FP CIT PET has been done. For that reason, this study compares the quality of F-18 FP CIT PET images reconstructed with different algorithms in terms of the recovery coefficient (RC), maximum PET counts, and binding potential (BP). The RCs of images were measured according to the National Electrical Manufacturers Association (NEMA) standard NU 4-2008 (NEMA NU4-2008). The PET images of the phantoms were reconstructed using various reconstruction algorithms (OSEM2D, FBP, 3DRP and OSEM3D/MAP) and filters. For the FBP reconstruction, the ramp, Butterworth (order: 1), Hamming, Hanning, Parzen, and SheppLogan filters were used. The cutoff frequency was 0.5 (even though the, ramp filter needed no cut-off frequency). For the OSEM3D/MAP reconstruction, various smoothing factors (β = 0.05, 0.5 and 1.5) were used with 18 iterations number. The β value was provided as a penalty function for constraint on neighboring voxels during the MAP algorithm. The β values of 0.05, 0.5 and 1.5 corresponded to predicted target resolutions of 1.5 mm, 2 mm, and 2.3 mm for the OSEM3D/MAP reconstruction algorithm, respectively. For the 3DRP reconstruction, Hanning filters were used. We used OSEM2D with 4 iterations and 16 subsets (default number in Siemens Inveon PET scanner) in this study for OSEM2D method. To compare the chosen parameters between the F-18 FP CIT PET images and phantoms, we used BALB nude mice (20 g body weight) were used to obtain mouse images. For evaluating the reconstruction methods, the maximum PET counts (counts/s/voxel) and BP (for image contrast ratio with striatum and cerebellum) of each reconstruction algorithm the striatal diameter of mice was observed to be 3 mm. Therefore, the RC values of the phantoms with a diameter of 3 mm were chosen. For phantoms with Φ = 3 mm, the OSEM2D provided the most appropriate 0.95 of RC value. Moreover, the maximum PET counts and the BP of the striatum with the OSEM2D reconstruction were observed to be high compared to the value for the other reconstruction methods. OSEM3D/MAP also showed high values for the maximum PET counts and the BP; however, the RC of OSEM3D/MAP (β = 0.05) exceeded 1 at Φ = 3 mm, and other OSEM3D/MAPs (β = 1.5 and 0.5) were lower than those of OSEM2D. Therefore, OSEM3D/MAP was not considered for decisions regarding the optimal reconstruction method. Through actual PET images we verified that the images with OSEM2D were identified more clearly and with higher image contrast. The OSEM2D reconstruction algorithm provided the best values (0.95) on reconstructed PET data; thus, OSE2D would be suitable for quantification of F-18 FP CIT PET images of mice obtained with a Siemens Inveon PET.

Evaluation of image quality and radiation dose in kilovoltage cone beam computed tomography

This study was to evaluate the image quality and radiation dose of kV-CBCT when varying mAs and reconstruction filter. The radiation dosimetry (CBDIw) and quality control of kV-CBCT image were done. Routine protocols in head, thorax, and pelvis protocols were performed as a reference image. Then the images were acquired with varied mAs, the other parameters were fixed. Each technique was reconstructed with different filter. The image quality in terms of low contrast and high contrast resolution including CBDIw were compared. The result found that the variation of mAs with auto filter affected low contrast resolution, but slightly effect high contrast resolution. When mAs increased, low contrast detectability increased. Decreasing one step of mAs (16.67%) kept in acceptable image quality and reduced about 15% of CBDIw. The smooth filter improved the low contrast resolution, but it decreased the high contrast resolution. While the sharp or ultra-sharp filter improved the high contrast resolution. In conclusion, the changing of mAs affects the low contrast resolution and CBDIW. While the reconstruction filter changed the both of low and high contrast resolution, but no effect to CBDIw. To optimize the image quality and radiation dose of routine protocols, mAs can reduce one step-down.

Robust actuator dynamics compensation method for real-time hybrid simulation

Abstract Real-time hybrid simulation (RTHS) is a practical, cost-effective, and versatile experimental technique to evaluate structural performance under dynamic excitation. The simulated structure is commonly split into a physically tested rate-dependent substructure (PS) and a numerically simulated substructure (NS). A transfer system such as a servo-hydraulic actuator is used to impose boundary conditions on the PS. Consequently, efficient actuator control is necessary to guarantee reliable simulation results. However, time delay and uncertainties exist due to the dynamics of the actuator, which adversely influence the accuracy and stability of RTHS. Therefore, an innovative robust actuator dynamics compensation method is proposed in this study comprising three components, namely a mixed sensitivity-based robust H∞ controller to stabilize the actuator–specimen dynamics, a polynomial extrapolation module to further cancel the actuator delay, and an adaptive filter for displacement reconstruction of the actuator–specimen system. A detailed design procedure of the proposed strategy is presented. The efficacy of the proposed strategy is validated through a series of virtual tests on the benchmark problem for RTHS. Results show that the proposed method exhibits excellent tracking performance and robustness. In particular, the maximum values of the calculated time delay (TD), root mean square of the tracking error (RMSE), and peak tracking error (PE) are 0 ms, 2.56%, and 2.12%, respectively, whereas the maximum values of the standard deviation of TD, RMSE, and PE are 0 ms, 0.25%, and 0.33%, respectively.

Real-Time Reconstruction for Low Contrast Ultrasonic Tomography Using Continuous-Wave Excitation

Two-phase flow widely exists in the process industry, where ultrasonic tomography provides reliable visualization with benefits of noninvasion, nonradiation, and low-cost. To provide real-time reconstruction of low acoustic impedance contrast medium distribution existed in two-phase flow, a novel approach using continuous-wave excitation is proposed. With the basic measurement model introduced, a subspace filtered reconstruction algorithm is introduced with improvements on both accuracy and speed. Through nonuniform shape constrained range filter, the relative image error (RE) is reduced by 32.94% and 33.03% compared to simultaneous algebraic reconstruction technique (SART) and filter back projection (FBP) methods. Through derivation of offline iteration/online reconstruction (OIOR) method and truncated singular value decomposition (TSVD), the computing speed increases to 122 frame/s, which fits the requirement of online monitoring. A prototype of the measurement system is introduced with improved design of bipolar high-voltage excitation module and fan-beam angle piezoelectric transducers. Qualitative and quantitative results show that the proposed method has better image accuracy compared to conventional methods.

Extraction of the cardiac waveform from simultaneous multislice fMRI data using slice sorted averaging and a deep learning reconstruction filter

Cardiac signal contamination has long confounded the analysis of blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). Cardiac pulsation results in significant BOLD signal changes, especially in and around blood vessels. Until the advent of simultaneous multislice echo-planar imaging (EPI) acquisition, the time resolution of whole brain EPI was insufficient to avoid cardiac aliasing (and acquisitions with repetition times (TRs) under 400–500 ms are still uncommon). As a result, direct detection and removal of the cardiac signal with spectral filters is generally not possible. Modelling methods have been developed to mitigate cardiac contamination, and recently developed techniques permit the visualization of cardiac signal propagation through the brain in undersampled data (e.g., TRs > 1s), which is useful in its own right for finding blood vessels. However, both of these techniques require data from which to estimate cardiac phase, which is generally not available for the data in many large databases of existing imaging data, and even now is not routinely recorded in many fMRI experiments.Here we present a method to estimate the cardiac waveform directly from a multislice fMRI dataset, without additional physiological measurements, such as plethysmograms. The pervasive spatial extent and temporal structure of the cardiac contamination signal across the brain offers an opportunity to exploit the nature of multislice imaging to extract this signal from the fMRI data itself. While any particular slice is recorded at the TR of the imaging experiment, slices are recorded much more quickly – typically from 10 to 20 Hz - sufficiently fast to fully sample the cardiac signal. Using the fairly permissive assumptions that the cardiac signal is a) pseudoperiodic b) somewhat coherent within any given slice, and c) is similarly shaped throughout the brain, we can extract a good estimate of the cardiac phase as a function of time from fMRI data alone. If we make further assumptions about the shape and consistency of cardiac waveforms, we can develop a deep learning filter to greatly improve our estimate of the cardiac waveform.

Efficient Bandwidth Estimation in 2D Filtered Backprojection Reconstruction.

A generalized cross-validation approach to estimate the reconstruction filter bandwidth in 2D filtered backprojection is presented. The method writes the reconstruction equation in equivalent backprojected filtering form, derives results on eigendecomposition of symmetric 2D circulant matrices, and applies them to make bandwidth estimation a computationally efficient operation within the context of standard backprojected filtering reconstruction. Performance evaluations on a range of simulated emission tomography experiments give promising results. The superior performance holds at both low and high total expected counts, pointing to the method's applicability even in weak signal-to-noise-ratio situations. The approach also applies to the more general class of elliptically symmetric filters, with the reconstructed estimate's performance often better than even that obtained with the true optimal radially symmetric filter.