Neural networks (NNs) have been widely applied in tomographic imaging through data-driven training and image processing. One of the main challenges using NNs real medical is requirement massive amounts data which are not always available clinical practice. In this paper, we demonstrate that, on contrary, one can directly execute reconstruction without data. The key idea to bring recently introduced deep prior (DIP) merge it with electrical impedance tomography (EIT) reconstruction. DIP...

Deep learning has recently been applied to electrical impedance tomography (EIT) imaging. Nevertheless, there are still many challenges that this approach face, e.g., targets with sharp corners or edges cannot be well recovered when using circular inclusion training data. This paper proposes an iterative-based inversion method and a convolutional neural network (CNN) based recover some challenging inclusions such as triangular, rectangular, lung shapes, where the CNN-based uses only random...

This paper presents an image reconstruction method based on parametric level set (PLS) using electrical impedance tomography. The conductivity to be reconstructed was assumed piecewise constant and the geometry of anomaly represented by a shape-based PLS function, which we represent Gaussian radial basis functions (GRBF). representation function significantly reduces number unknowns, circumvents many difficulties that are associated with traditional (TLS) methods, such as regularization,...

Electrical impedance tomography (EIT) is highly sensitive to modelling errors that arise from model reductions and inaccurate knowledge of auxiliary parameters such as electrode positions, contact impedances boundary shape the body. In difference imaging, where objective reconstruct change in conductivity between EIT measurements at two time instants, traditional way circumvent using a global linearization nonlinear forward problem. Recently, reconstruction approach for imaging was proposed...

This paper presents a novel difference imaging approach based on the recently developed parametric level set (PLS) method for estimating change in target conductivity from electrical impedance tomography measurements. As conventional imaging, reconstruction of is data sets measured surface body before and after change. The key feature proposed that to be reconstructed assumed piecewise constant, while geometry anomaly represented by shape-based PLS function employing Gaussian radial basis...

To evaluate the recently proposed nonlinear difference imaging approach to electrical impedance tomography (EIT) in realistic 3-D geometries.In this paper, feasibility of approach-based EIT is tested using simulation studies geometries thorax and larynx, with an experimental study a thorax-shaped water tank. All test cases exhibit severe modeling errors due uncertainty boundary shape body.In all cases, conductivity change reconstructed outperforms conventional reconstructions qualitatively...

A statistical shape-constrained reconstruction (SSCR) framework is presented to incorporate the prior information of human lung shapes for electrical impedance tomography. The extracted from 8000 chest-computed tomography scans across 800 patients. implemented with two approaches-a one-step SSCR and an iterative in imaging. provides fast high accurate reconstructions healthy lungs, whereas allows simultaneously estimate pre-injured injury part. approaches are evaluated simulated examples...

This article proposes a frequency security constrained unit commitment (FSC-UC) model for sufficient deployment of diversified support resources. Specifically, the diversities in generators' inertial response capability, primary (PFR) ramping and quasi-steady-state (QSS) PFR power capability are integrated into FSCs to ensure post-contingency security. Moreover, we analyze opposite impacts upper/lower variable renewable energy (VRE) deviation, brought by VRE uncertainties, on Hence, an...

Abstract Information storage and security are the building blocks of information age. Optical is a low‐cost, robust, high‐capacity technique. Discovering new optical media techniques with beyond binary capacity enhanced in demand. Here beyond‐binary, “burn after read” rewritable multiplexing encryption method demonstrated via Ce:YAG trapping states. It found that thermo‐luminescence (TL) intensity states writing light power dependent, enabling multi‐gray‐level encoding.A strategy to encode...

Electrical impedance tomography (EIT) is an imaging modality that provides cross-sectional images of objects carry contrasts in electrical conductivity. EIT suitable for example monitoring industrial processes involving multiple phases with different conductivities. This paper presents a parametric level set (PLS) based reconstruction scheme EIT-imaging conductivity distributions within multiphase systems. The proposed involves applying model to solve the inverse problem finding interfaces...

This paper presents a new computational framework in electrical impedance tomography (EIT) for shape reconstruction based on the concept of moving morphable components (MMC). In proposed framework, problem is solved an explicit and geometrical way. Compared with traditional pixel or shape-based solution can incorporate more geometry prior information into topology optimization directly therefore render process flexibility. It also has afford potential to substantially reduce burden...

This paper proposes a novel approach to reconstruct changesin target conductivity from electrical impedance tomography measurements.As in the conventional difference imaging,the reconstruction of change is based on potential measurementsfrom exterior boundary before and after change.In this paper, however, images conductivitybefore are reconstructed simultaneously two data sets.The key feature that parameterized as linear combination initial state change.This allows for modeling...

This paper presents a B-spline-based shape reconstruction approach for electrical impedance tomography (EIT). In the proposed approach, conductivity distribution to be reconstructed is assumed piecewise constant. The geometry of inclusions parameterized using B-spline curves, and EIT forward solver modified as set control points representing inclusions' boundary data on domain boundary. low-order representation decreases computational demand reduces ill-posedness problem. performance tested...

This paper presents a parametric level set-based reconstruction method for nonstationary applications using electrical impedance tomography (EIT). Due to relatively low signal-to-noise ratios in EIT measurement systems and the diffusive nature of EIT, reconstructed images often suffer from spatial resolution. In addressing these challenges, we propose computationally efficient shape-estimation approach where conductivity distribution be is assumed piecewise constant, region boundaries are...

This study presents a computed tomography (CT) image-guided electrical impedance (EIT) method for medical imaging. CT is robust imaging modality accurately reconstructing the density structure of region being scanned. EIT can detect abnormalities to which scans may be insensitive, but poor spatial resolution major concern applications. A cross-gradient has been introduced oil and gas exploration jointly invert multiple geophysical datasets associated with different medium properties in same...

In this work, we propose a new shape reconstruction framework rooted in the concept of Boolean operations for electrical impedance tomography (EIT). Within framework, evolution inclusion shapes and topologies are simultaneously estimated through an explicit boundary description. For this, use B-spline curves as basic primitives topology optimization. The effectiveness proposed approach is demonstrated using simulated experimentally-obtained data (testing EIT lung imaging). study, improved...

Electrical impedance tomography (EIT) is a powerful tool for nondestructive evaluation, state estimation, and process tomography, among numerous other use cases. For these applications, in order to reliably reconstruct images of given using EIT, we must obtain high-quality voltage measurements from the target interest. As such, it obvious that locations electrodes used measuring play key role this task. Yet, date, methods optimally placing either require knowledge on EIT (which is, practice,...

This paper introduces "LLMSeamCarver," a LLM-enhanced methodology for image resizing. LLMSeamCarver addresses the limitations of traditional seam carving with static pre-defined parameters, it uses LLM to achieve dynamic and user-controlled dynamically-resizing images.The inclusion LLMs in this research facilitates optimization parameter tuning adaptive energy function adjustments, enhancing overall robustness efficiency emerges as transformative tool, offering versatile, high-quality resized images.

This paper introduces "LLMSeamCarver," a LLM-enhanced methodology for image resizing. LLMSeamCarver addresses the limitations of traditional seam carving with static pre-defined parameters, it uses LLM to achieve dynamic and user-controlled dynamically-resizing images.The inclusion LLMs in this research facilitates optimization parameter tuning adaptive energy function adjustments, enhancing overall robustness efficiency emerges as transformative tool, offering versatile, high-quality resized images.

This paper presents the implementation of a high-resolution time-to-digital converter (TDC), which is adapted to varying environmental conditions. The TDC implemented in field-programmable gate arrays (FPGA), using carry chains achieve fine time measurement. Multiple are integrated single channel for resolution enhancement. performance would suffer greatly without temperature compensation due its sensitivity operating temperature. In order improve adaptability, we analyzed...

A B-spline level set (BLS) based method is proposed for shape reconstruction in electrical impedance tomography (EIT). We assume that the conductivity distribution to be reconstructed piecewise constant, transforming image problem into a problem. The shape/interface of inclusions implicitly represented by function (LSF), which modeled as continuous parametric expressed using functions. Starting from modeling with LSF, we show allows us compute solution restricting minimization space spanned...

This work proposes a novel shape-driven reconstruction approach for difference electrical impedance tomography (EIT). In the proposed approach, problem is formulated as shape and solved via an explicit geometrical methodology, where geometry of embedded inclusions represented by topology description function (STDF). To incorporate more prior information directly into to provide better flexibility in solution process, concept moving morphable component (MMC) applied here implying that MMC...

Reactions of N-diphenylphosphanylmethyl-4-aminopyridine (dppmapy) with K[Ag(CN)2], Ag(dca) (dca = dicyanamide), AgSCN, AgCl, AgBr or AgI gave rise to six [Ag2X2]-based (X CN−, dca, SCN−, Cl−, Br− and I−) compounds, [{Ag2(CN)2(dppmapy)}·0.5CHCl3]n (1), [Ag2L2(dppmapy)2]n (2: L dca; 3: SCN), [{Ag2L2(dppmapy)2}·sol]n (4: Cl, sol 0.5MeOH·0.5CH2Cl2; 5: Br, 2CHCl3), [Ag2I2(dppmapy)4]·3MeOH (6). Complexes 1–6 were characterized by elemental analysis, IR, powder X-ray diffraction (PXRD), single...