Quasi-phasematching of harmonic generation via multimode beating in waveguides

A new scheme for quasi-phasematching high harmonic generation (HHG) in gases is proposed. In this, the rapid variation of the axial intensity resulting from excitation of more than one mode of a waveguide is used to achieve quasi phasematching. Numerical modeling demonstrates enhancement of the harmonic signal over that achieved for a single coherence length by factors >10^4.Comment: 6 pages including 3 figure

Simulation and beyond – Principles of effective obstetric training

Simulation training provides a safe, non-judgmental environment where members of the multi-professional team can practice both their technical and non-technical skills. Poor teamwork and communication are recurring contributing factors to adverse maternal and neonatal outcomes. Simulation can improve outcomes and is now a compulsory part of the national training matrix. Components of successful training include involving the multi-professional team, high fidelity models, keeping training on-site, and focussing on human factors training; a key factor in adverse patient outcomes. The future of simulation training is an exciting field, with the advent of augmented reality devices and the use of artificial intelligence

Radiation-Pressure Acceleration of Ion Beams from Nanofoil Targets: The Leaky Light-Sail Regime

A new ion radiation-pressure acceleration regime, the "leaky light sail," is proposed which uses sub-skin-depth nanometer foils irradiated by circularly polarized laser pulses. In the regime, the foil is partially transparent, continuously leaking electrons out along with the transmitted laser field. This feature can be exploited by a multispecies nanofoil configuration to stabilize the acceleration of the light ion component, supplementing the latter with an excess of electrons leaked from those associated with the heavy ions to avoid Coulomb explosion. It is shown by 2D particle-in-cell simulations that a monoenergetic proton beam with energy 18 MeV is produced by circularly polarized lasers at intensities of just 10(19) W/cm(2). 100 MeV proton beams are obtained by increasing the intensities to 2 x 10(20) W/cm(2)

AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

During pregnancy, ultrasound examination in the second trimester can assess fetal size according to standardized charts. To achieve a reproducible and accurate measurement, a sonographer needs to identify three standard 2D planes of the fetal anatomy (head, abdomen, femur) and manually mark the key anatomical landmarks on the image for accurate biometry and fetal weight estimation. This can be a time-consuming operator-dependent task, especially for a trainee sonographer. Computer-assisted techniques can help in automating the fetal biometry computation process. In this paper, we present a unified automated framework for estimating all measurements needed for the fetal weight assessment. The proposed framework semantically segments the key fetal anatomies using state-of-the-art segmentation models, followed by region fitting and scale recovery for the biometry estimation. We present an ablation study of segmentation algorithms to show their robustness through 4-fold cross-validation on a dataset of 349 ultrasound standard plane images from 42 pregnancies. Moreover, we show that the network with the best segmentation performance tends to be more accurate for biometry estimation. Furthermore, we demonstrate that the error between clinically measured and predicted fetal biometry is lower than the permissible error during routine clinical measurements

AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes

During pregnancy, ultrasound examination in the second trimester can assess fetal size according to standardized charts. To achieve a reproducible and accurate measurement, a sonographer needs to identify three standard 2D planes of the fetal anatomy (head, abdomen, femur) and manually mark the key anatomical landmarks on the image for accurate biometry and fetal weight estimation. This can be a time-consuming operator-dependent task, especially for a trainee sonographer. Computer-assisted techniques can help in automating the fetal biometry computation process. In this paper, we present a unified automated framework for estimating all measurements needed for the fetal weight assessment. The proposed framework semantically segments the key fetal anatomies using state-of-the-art segmentation models, followed by region fitting and scale recovery for the biometry estimation. We present an ablation study of segmentation algorithms to show their robustness through 4-fold cross-validation on a dataset of 349 ultrasound standard plane images from 42 pregnancies. Moreover, we show that the network with the best segmentation performance tends to be more accurate for biometry estimation. Furthermore, we demonstrate that the error between clinically measured and predicted fetal biometry is lower than the permissible error during routine clinical measurements

BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes

Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometry estimation depends on the precise detection of landmarks in standard ultrasound planes. Manual annotation can be time-consuming and operator dependent task, and may results in high measurements variability. Existing methods for automatic fetal biometry rely on initial automatic fetal structure segmentation followed by geometric landmark detection. However, segmentation annotations are time-consuming and may be inaccurate, and landmark detection requires developing measurement-specific geometric methods. This paper describes BiometryNet, an end-to-end landmark regression framework for fetal biometry estimation that overcomes these limitations. It includes a novel Dynamic Orientation Determination (DOD) method for enforcing measurement-specific orientation consistency during network training. DOD reduces variabilities in network training, increases landmark localization accuracy, thus yields accurate and robust biometric measurements. To validate our method, we assembled a dataset of 3,398 ultrasound images from 1,829 subjects acquired in three clinical sites with seven different ultrasound devices. Comparison and cross-validation of three different biometric measurements on two independent datasets shows that BiometryNet is robust and yields accurate measurements whose errors are lower than the clinically permissible errors, outperforming other existing automated biometry estimation methods. Code is available at https://github.com/netanellavisdris/fetalbiometry

The reflectivity of relativistic ultra-thin electron layers

The coherent reflectivity of a dense, relativistic, ultra-thin electron layer is derived analytically for an obliquely incident probe beam. Results are obtained by two-fold Lorentz transformation. For the analytical treatment, a plane uniform electron layer is considered. All electrons move with uniform velocity under an angle to the normal direction of the plane; such electron motion corresponds to laser acceleration by direct action of the laser fields, as it is described in a companion paper. Electron density is chosen high enough to ensure that many electrons reside in a volume \lambda_R^3, where \lambda_R is the wavelength of the reflected light in the rest frame of the layer. Under these conditions, the probe light is back-scattered coherently and is directed close to the layer normal rather than the direction of electron velocity. An important consequence is that the Doppler shift is governed by \gamma_x=(1-(V_x/c)^2)^{-1/2} derived from the electron velocity component V_x in normal direction rather than the full \gamma-factor of the layer electrons.Comment: 7 pages, 4 figures, submitted to the special issue "Fundamental Physics with Ultra-High Fields" in The European Physical Journal