Regularizing the inverse problem of ultrasound beamforming with non-local structure tensor total variation.

Researchers are increasingly interested in using inverse problem methodologies for ultrasound image reconstruction instead of conventional beamforming methods, termed the inverse problem of ultrasound beamforming (IPB). This new imaging method promises to increase the frame rate of plane-wave imaging by enabling the reconstruction of high-quality images from fewer plane-wave transmissions compared to conventional beamforming methods. IPB assumes that the RF signals received by the ultrasound probe are linearly related to the beamformed image.

In Vitro and In Vivo Photothermal and Photoacoustic Activities of Polymeric Nanoparticles Loaded with Nickel, Palladium, and Platinum-Bis(dithiolene) Complexes.

The development of nanosystems with enhanced photothermal and photoacoustic properties is crucial for advancing theranostic applications in cancer therapy. This study explores polymeric nanoparticles (NPs) constituted by a biocompatible poly(ethylene glycol)-block-poly(benzyl malate) copolymer and loaded with metal-bis(dithiolene) complexes (M = Ni, Pd, Pt). These NPs, prepared via a robust nanoprecipitation method, demonstrate uniform morphology, efficient encapsulation (≈70%), and tailored near-infrared (NIR) optical absorption properties.

Computationally Efficient SVD Filtering for Ultrasound Flow Imaging and Real-Time Application to Ultrafast Doppler.

Over the past decade, ultrasound microvasculature imaging has seen the rise of highly sensitive techniques, such as ultrafast power Doppler (UPD) and ultrasound localization microscopy (ULM). The cornerstone of these techniques is the acquisition of a large number of frames based on unfocused wave transmission, enabling the use of singular value decomposition (SVD) as a powerful clutter filter to separate microvessels from surrounding tissue. Unfortunately, SVD is computationally expensive, hampering its use in real-time UPD imaging and weighing down the ULM processing chain, with evident impact in a clinical context.

Boosting Cardiac Color Doppler Frame Rates With Deep Learning.

Color Doppler echocardiography enables visualization of blood flow within the heart. However, the limited frame rate impedes the quantitative assessment of blood velocity throughout the cardiac cycle, thereby compromising a comprehensive analysis of ventricular filling. Concurrently, deep learning is demonstrating promising outcomes in postprocessing of echocardiographic data for various applications.

Investigating the three-dimensional myocardial micro-architecture in the laminar structure using X-ray phase-contrast microtomography.

A comprehensive grasp of the myocardial micro-architecture is essential for understanding diverse heart functions. This study aimed to investigate three-dimensional (3D) cardiomyocyte arrangement in the laminar structure using X-ray phase-contrast microtomography. Using the ID-19 beamline at the European Synchrotron Radiation Facility, we imaged human left ventricular (LV) wall transparietal samples and reconstructed them with an isotropic voxel edge length of 3.