Fine-grained classification of cervical cells into different abnormality levels is great clinical importance but remains very challenging. Contrary to the traditional methods that rely on hand-crafted or engineered features, convolution neural network (CNN) can classify based automatically learned deep features. However, CNN in previous studies does not involve cell morphological information, and it unknown whether features be directly modeled by cells. This paper presents a CNN-based method...

A multibranch Rao–Wilton–Glisson (MB-RWG) basis function is proposed in this article, which composed of one positive triangle with a larger edge length and several negative triangles smaller lengths. All are aggregated to replace the traditional RWG function, exactly same expression defined on triangles. The number can be changed different mesh structures. Similar functions, MB-RWG functions guarantee normal current continuity across common edges. No line charges exist total charge zero....

Diffusion bridges (DBs) are a class of diffusion models that enable faster sampling by interpolating between two paired image distributions. Training traditional DBs for reconstruction requires high-quality reference images, which limits their applicability to settings where such references unavailable. We propose SelfDB as novel self-supervised method training directly on available noisy measurements without any images. formulates the process further sub-sampling additional times and neural...

The reservoir physical parameters (such as porosity, permeability, phase etc.) will change in the process of water injection development with continuous flushing effect high magnification drive, which may have adverse effects on if they cannot be accurately characterized. In this paper, we try to quantitative characterize time -varying features pore structure from microscopic perspective. We used high-resolution 3D micro-CT (MCT) images supplement analysis properties rocks, and network...

It is required to calculate the stored reactive energy of an antenna in order evaluate its Q factor.Although it has been investigated for a long time, some issues still need further clarification.The main difficulty involved that tends become infinitely large when integrating conventionally defined density whole space outside small sphere containing antenna.The usually made be bounded by subtracting additional term associated with radiation fields.However, there exists no well-accepted...

The mechanical and electrical properties of soft tissues are relative to tissues' pathological state. Modern medical imaging devices have shown a trend multi-modal imaging, which will provide complementary functional information improve the accuracy disease diagnosis. However, no method or system can simultaneously measure tissue. In this study, we proposed novel dual-modal integrated by shear wave elasticity (SWEI) Magneto-acousto-electrical tomography (MAET) tissue's conductivity...

Mechanophores (MPs) undergo chemical reactions to become fluorescent in response a mechanical stimulus that reflects the magnitude and distribution of applied stress. MPs are an emerging technology for self‐reporting damage sensing applications polymeric materials aeronautical, energy generation, automotive industries. However, quantitative calibration MP local stresses remains outstanding challenge. Herein, method calibrate intensity activation ( I ) with hydrostatic σ h is presented....

There are several formulations for calculating the Q factors of antennas. The evaluated not always in agreement because differences definition factor and method addressing stored reactive energies. This paper gives a short comparison five them with numerical examples.

ABSTRACT Human recombinant Fab fragments specific for the spike protein of severe acute respiratory syndrome coronavirus (SARS-CoV) were screened from a human library, which was generated RNAs peripheral lymphocytes convalescent SARS patients. Among 50 randomly picked clones, 12 Fabs specially reacted with S by an enzyme-linked immunosorbent assay. The microneutralizing test showed that one clone, designated M1A, had neutralizing activity on Vero E6 cells against SARS-CoV. DNA sequence...

A quasi-Helmholtz decomposition with loop-star basis functions including multibranch Rao-Wilton-Glisson (MB-RWG) is proposed for electromagnetic scattering problems on an object multiple surfaces. The loop and star in the interior region of each surface are generated RWG functions, those at bordering lines between different surfaces constructed MB-RWG functions. With scheme can be applied to two adjacent mesh resolutions directly. Some numerical examples presented low frequencies verify...

Mechanoresponsive molecules called mechanophores fluoresce when they experience sufficient force. By incorporating into the matrix of a rigid particle reinforced composite, local stress concentrations in polymer around can be seen by fluorescence microscopy. Further details found article number 2101080 Chelsea S. Davis and co-workers.

Parallel magnetic resonance imaging (MRI) is a widely-used technique that accelerates data collection by making use of the spatial encoding provided multiple receiver coils. A key issue in parallel MRI estimation coil sensitivity maps (CSMs) are used for reconstructing single high-quality image. This paper addresses this developing SS-JIRCS, new self-supervised model-based deep-learning (DL) method image reconstruction equipped with automated CSM calibration. Our deep network consists three...

The application of multibranch Rao-Wilton-Glisson (MB-RWG) basis function in analyzing electromagnetic scatterings from perfect electrically conducting (PEC) targets is presented this paper. MB-RWG functions have the properties RWG to expand surface currents. Moreover, can be defined on boundary between two surfaces with different mesh resolutions. branch number varies according element sizes adjacent surfaces. Hence, flexibly used integral equations. Numerical results verified versality functions.

In this communication, a multibranch Schaubert–Wilton–Glisson (MB-SWG) basis function is proposed for solving volume integral equations (VIEs) involved in electromagnetic scattering problems. MB-SWG defined on several tetrahedrons the positive and negative parts that share common triangular face, replacing two traditional (SWG) function. The convenient domain decomposition with coarse mesh scheme one subdomain fine neighboring domains. Numerical results confirm accuracy versatility of...

Diffusion bridges (DB) have emerged as a promising alternative to diffusion models for imaging inverse problems, achieving faster sampling by directly bridging low- and high-quality image distributions. While incorporating measurement consistency has been shown improve performance, existing DB methods fail maintain this in blind where the forward model is unknown. To address limitation, we introduce ADOBI (Adaptive Bridge Inverse Problems), novel framework that adaptively calibrates unknown...

Fine-grained classification of cervical cells into different abnormality levels is great clinical importance but remains very challenging. Contrary to traditional methods that rely on hand-crafted or engineered features, convolution neural network (CNN) can classify based automatically learned deep features. However, CNN in previous studies do not involve cell morphological information, and it unknown whether features be directly modeled by cells. This paper presents a CNN-based method...

Multibranch basis functions have been confirmed to be effective for local refinement of domain decomposition methods in the application solving surface and volume integral equations. Surface-volume equations (SVIEs) are applied hybrid electromagnetic scattering problems involving perfect electric conductors (PEC) dielectrics, especially inhomogeneous anisotropic media. In this paper, multibranch Rao-Wilton-Glisson (MB-RWGs) conjunction with Schaubert-Wilton-Glisson (MB-SWGs) SVIEs. Block...

We develop a self-supervised and physics-guided deep unfolding (DU) network for MR image reconstruction by weighting the k-space sampling Density in training Loss (wDeLo). have demonstrated that high-quality images at spatial resolution of 0.6x0.6x0.8 mm3 could be achieved using an acquisition time 1 minute (x6.25 acceleration) or 45 seconds (8x acceleration). Compared to SSDU its uniform weighted counterpart (un-wDeLo), wDeLo method significantly improves PSNR SSIM. It had fewer artifacts,...

Motivation: Dynamic contrast-enhanced (DCE) MRI faces challenges from respiratory motion and sub-optimal DCE contrast timing. Free-breathing with high temporal resolution is desirable. Goal(s): We aim to reconstruct motion-free DCE-MRI. Approach: proposed a Motion Integrated Forward model using vector fields jointly estimated coil sensitivity severely under-sampled data. Furthermore, we utilized model-based deep learning framework amalgamate the knowledge of measurement denoising prior....