Determining the nature of orbital tumors is challenging for current imaging interpretation methods, which hinders timely treatment. This study aimed to propose an end-to-end deep learning system automatically diagnose tumors. A multi-center dataset 602 non-contrast-enhanced computed tomography (CT) images were prepared. After image annotation and preprocessing, CT used train test (DL) model following two stages: tumor segmentation classification. The performance on testing set was compared...

We propose a novel seismic signal processing approach to efficiently and effectively attenuate random noises. The proposed is generalized noise attenuation solution that can be applied typical denoising operators. Our work has two main contributions. First, conventional filtering operators "regularize" the denoised results through operator design. However, as data have strong nonstationarity, it inevitable remove certain components. resampling mechanism alleviates loss. Second, operation...

A technology for non-intrusive real-time structural health monitoring using piezoelectric active sensors is presented. The approach based on variations of the coupled electromechanical impedance patches bonded to metallic structures in high-frequency bands. In each these applications, a single element used as both an actuator and sensor. resulting coupling makes frequency-dependent electric spectrum PZT sensor good mapping underlying structure’s acoustic signature. Moreover, incipient damage...

By building an adaptive filter bank, the empirical wavelet transform (EWT) decomposes analyzed signal into several intrinsic mode functions (IMFs). Although some applications have certified effectiveness of EWT, EWT is affected obviously when analyzing nonstationary signals (e.g., seismic data). In this letter, we propose improved (IEWT) to decompose a IMFs and describe its frequency features. After computing Fourier spectrum signal, scale-space representation (SSR) used extract slowly...

Seismic attenuation estimation is a significant task for characterizing reservoirs and improving the resolution of seismic data. The logarithmic spectral ratio (LSR) one widely used tools estimation. However, how to select suitable frequency bandwidth LSR difficult task, especially field Moreover, data are often contained kinds noises, which makes unstable. We proposed an enhanced (ELSR) workflow estimate attenuation. First, we built sparse S-transform (SST) obtain time-frequency (TF)...

Random noise suppression is of great importance in seismic processing and interpretation, time–frequency peak filtering (TFPF) a classic denoising approach. In TFPF, pseudo Wigner–Ville distribution (PWVD) used to linearise the given signal for an unbiased estimation instantaneous frequency. However, window length trade-off parameter preserving valid signals attenuating random noise. A long may cause loss desired signal, whereas short be inadequate suppress To ensure good between...

Characterization of seismic geologic structures, such as describing fluvial channels and faults, is significant for reservoir prediction. The coherence algorithm one the widely used techniques discontinuous structures. However, precise attributes between adjacent traces are difficult to compute due nonstationary non-Gaussian property data. To describe structures accurately, we define a high-order spectrum-coherence (HOSC) attribute. First, have developed time-frequency (TF) analysis method...

Time–frequency analysis (TFA) technology plays a significant role in seismic signal processing. The time–frequency representation (TFR) calculated using the TFA method is helpful for localization of time-varying frequencies within signal. Nevertheless, limited by Heisenberg uncertainty principle, traditional linear methods always provide blurred TFRs, which makes them difficult to distinguish details structures. Recently, synchrosqueezing transform (SST) was designed improve concentration...

Geologic structure characterization is a key step for seismic interpretation, such as fluvial channels, faults, and fractures. The coherence attribute widely used tool describing discontinuities, which usually calculated based on the similarity dissimilarity of adjacent traces. However, accurately extracting difficult task in field data applications because signal one typical nonstationary, non-Gaussian, wideband signals. To describe discontinuities at different scales, we propose workflow...

The instantaneous frequency (IF) is an important feature for the analysis of nonstationary signals. For IF estimation, time–frequency representation (TFR)-based algorithm used in a common class methods. TFR-based methods always need concentrated around “true” IFs and number components within signal. In this paper, we propose novel method to adaptively estimate signals, even weak proposed technique not based on TFR: it estimation operator (FEO), short-time Fourier transform (STFT) as its...

The fractional parameter in a generalized model is set to control the degree of absorption. However, it does not have an explicit physical meaning, even though may be estimated from seismic data. Therefore, necessary establish common reference, which physically significant for applications. In this paper, reference presented according constant Q model. proposed can used analyze different value interval ranges. When small, related absorptive mechanism equivalent large, reveals attenuation...

Traditional coherence algorithms are mostly based on the assumption that seismic traces Gaussian and linear correlative. However, for nonGaussian traces, correlation analysis cannot accurately describe similarity between adjacent traces. To solve this issue, we adopt kernel instead of to improve coherence-based algorithms. Note is a generalized with various functions. It provides framework expanding algorithm correlation. Moreover, discuss how choose an appropriate function in detail....

In this letter, we concern the acoustic impedance (AI) inversion from known reflectivity based on increasingly mature deconvolution techniques. For seismic data with complicated geological structures, first construct regularization model for AI proposed regularizer consisting of total variation (TV) seminorm and Frobenius norm Hessian. Second, develop split Bregman (SB) iterative algorithm in frequency domain solving model. Finally, verify effectiveness our method via synthetic field data....

Random noise elimination acts as an important role in the seismic data processing. Moreover, protecting and recovering useful subsurface structure information are also significant. In this study, S-mean that can obtain geometric mean of traces on symmetric positive definite (SPD) matrix manifold is adopted a nonlinear filter for denoising. Furthermore, has best correlation with other elements based S-divergence due to optimization finding SPD manifold. Therefore, broken features noisy...

In natural reservoir rocks, fabric heterogeneity can further induce heterogeneous geometrical distribution of immiscible multi-phase fluid mixture, since migration may be affected by lithological variation (mainly permeability) in geological time scales, causing patchy saturation fluids. Both structure and patchy-saturation lead to strong seismic wave dispersion attenuation. this work, a double double-porosity model is presented describe the overlapping effect two heterogeneities on The...

Classical adaptive filtering algorithms with a diffusion strategy under the mean square error (MSE) criterion can face difficulties in distributed estimation (DE) over networks complex noise environment, such as non-zero non-Gaussian noise, object of ensuring robust performance. In order to overcome limitations, this paper proposes novel algorithm, which is developed by using variable center generalized maximum Correntropy (GMCC-VC). Generalized first defined introducing original...

Microwave imaging problems are nonlinear and ill-posed due to multiple scattering a lack of observed data. The optimization method with total variation (TV) regularization can be used address the problems. However, TV is susceptible staircase effect, which blurs edges. In order alleviate in this study, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\boldsymbol{\mathrm{L}^{\mathrm{p}}}$</tex> -norm as factor applied subspace-based method,...

Crystals and microstructure array electrodes are designed to affect the propagation of light beam. The apply an external voltage that changes electric field spatial distribution crystal refractive index guide beam deflection. There less studies on electro-optic deflectors based KTP crystals in market. Moreover, existing deflection has low accuracy poor stability. To overcome this problem above, electro-optical model with different electrode structures proposed paper. Through detailed...

Summary Traditional coherence algorithms most rely on the basic assumption that relationship between seismic traces is linear and obeys Gaussian distribution. However, in practice, correlation usually nonlinear, are non-Gaussian signals. The canonical analysis (CCA) cannot describe similarity adjacent detail. To overcome this problem improve resolution robustness of algorithm, we introduce kernelized instead C3 algorithm. Note a generalized with various kernel functions. Then, discuss how to...

In <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , the grant number in first footnote for National Postdoctoral Program Innovative Talents should be BX20190279.

Summary One of the key works for seismic interpretation is to characterize geological structures, such as fluvial channels and faults. The coherence attribute an effective tool characterizing However, extracting accurate attributes between adjacent traces difficult due non-stationary, non-Gaussian, wide-band properties field data. To overcome this issue, we propose a multi-scale (MSC) workflow. We first introduce multi-channel variational mode decomposition (MVMD) decompose data into...

Biological tissue preparation materials such as salt, gelatin, edible alkali, cornmeal and glucose are used to configure the brain experimental model in order study interaction between microwave. Different physiological tissues, skin, spinal cord, gray matter, etc., can be formulated using different composite according characteristics of electrical parameters tissue. The accuracy simulation experiment was verified with help a simulated bionic model. In detection biological based on...