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2-D sparse arrays may push the development of low-cost 3-D systems, not needing to control thousands of elements by expensive application-specific integrated circuits (ASICs). However, there is still some concern about their suitability in applications, such as Doppler investigation, which inherently involve poor signal-to-noise ratios (SNRs). In this article, a novel real-time 3-D pulsed-wave (PW) Doppler system, based on a 256-element 2-D spiral array, is presented. Coded transmission (TX) and matched filtering were implemented to improve the system SNR. Standard sonograms as well as multigate spectral Doppler (MSD) profiles, along lines that can be arbitrarily located in different planes, are presented. The performance of the system was assessed quantitatively on experimental data obtained from a straight tube flow phantom. An SNR increase of 11.4 dB was measured by transmitting linear chirps instead of standard sinusoidal bursts. For a qualitative assessment of the system performance in more realistic conditions, an anthropomorphic phantom of the carotid arteries was used. Finally, real-time B-mode and MSD images were obtained from healthy volunteers.
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http://dx.doi.org/10.1109/TUFFC.2021.3051628 | DOI Listing |
Proc Natl Acad Sci U S A
September 2025
Molecular Imaging Program at Stanford, Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA 94304.
The biophysical properties of single cells are crucial for understanding cellular function and behavior in biology and medicine. However, precise manipulation of cells in 3-D microfluidic environments remains challenging, particularly for heterogeneous populations. Here, we present "Electro-LEV," a unique platform integrating electromagnetic and magnetic levitation principles for dynamic 3-D control of cell position during separation.
View Article and Find Full Text PDFNat Commun
August 2025
Department of Earth Sciences, University of Geneva, Geneva, Switzerland.
Volcanic risk escalates significantly during unrest. In late 2021, the Italian island of Vulcano entered into a phase of unrest featuring Very Long Period seismic events, which are considered to be markers of magma and gas flowing across the volcanic plumbing system. Here we show how Neural Network Nodal Ambient Noise Tomography generates a high-resolution shear-wave velocity model for investigating the causative drivers of Vulcano's unrest.
View Article and Find Full Text PDFMeat Sci
August 2025
Key Laboratory of Clean Energy in Western Jilin Province, College of Chemistry, Baicheng Normal University, Baicheng 137000, China. Electronic address:
To investigate the preservation effects of active intelligent packaging film (S/P/A/T film) incorporated with anthocyanins (AMA) and tea polyphenols (TP) on meat, pork was selected as a representative sample, and preservation and monitoring experiments were conducted at 4 °C. The antimicrobial properties of the S/P/A/T active intelligent packaging were confirmed by observing the effects of the film solution on the growth curves and bacterial morphology of S. aureus and E.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
July 2025
Stroke is a leading contributor to long-term disability worldwide, and rehabilitation often relies on costly devices, limited infrastructure, or labor-intensive protocols. While virtual reality-based exergames have gained popularity for promoting patient engagement, most rely on proprietary sensors or wearable electronics, limiting accessibility and clinical adaptability. This study presents the design, implementation, and pilot evaluation of a custom exergame that estimates the 3D elbow angle using a single RGB camera and two colored spheres as markers, eliminating the need for specialized hardware.
View Article and Find Full Text PDFJ Am Coll Radiol
July 2025
Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; Past Chair, Executive Committee for the Society of Imaging Informatics in Medicine; Director, 3-D and Advanced Imaging Laboratory, Center for Practice Transformation in Radiology at the University of Pen
Radiology education is challenged by increasing clinical workloads, limiting trainee supervision time and hindering real-time feedback. Large language models (LLMs) can enhance radiology education by providing real-time guidance, feedback, and educational resources while supporting efficient clinical workflows. We present an interpretation-centric framework for integrating LLMs into radiology education subdivided into distinct phases spanning predictation preparation, active dictation support, and postdictation analysis.
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