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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Jensen, Jørgen Arendt
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (26/26 displayed)
- 2023Contrast-enhanced ultrasound imaging using capacitive micromachined ultrasonic transducerscitations
- 2022A Hand-Held 190+190 Row–Column Addressed CMUT Probe for Volumetric Imagingcitations
- 20213D printed calibration micro-phantoms for super-resolution ultrasound imaging validationcitations
- 2020Real Time Synthetic Aperture and Plane Wave Ultrasound Imaging with the Xilinx VERSAL™ SIMD-VLIW Architecturecitations
- 2019Imaging Performance for Two Row–Column Arrayscitations
- 2019188+188 Row–Column Addressed CMUT Transducer for Super Resolution Imagingcitations
- 2019CMUT Electrode Resistance Design: Modelling and Experimental Verification by a Row-Column Arraycitations
- 20193D Printed Calibration Micro-phantoms for Validation of Super-Resolution Ultrasound Imagingcitations
- 2018Probe development of CMUT and PZT row-column-addressed 2-D arrayscitations
- 2018Increasing the field-of-view of row–column-addressed ultrasound transducers: implementation of a diverging compound lenscitations
- 2018Design of a novel zig-zag 192+192 Row Column Addressed Array Transducer: A simulation study.citations
- 2017Transmitting Performance Evaluation of ASICs for CMUT-Based Portable Ultrasound Scanners
- 2017Real-time Implementation of Synthetic Aperture Vector Flow Imaging on a Consumer-level Tabletcitations
- 2017Output Pressure and Pulse-Echo Characteristics of CMUTs as Function of Plate Dimensionscitations
- 20163-D Vector Flow Using a Row-Column Addressed CMUT Arraycitations
- 20153-D Imaging Using Row–Column-Addressed Arrays With Integrated Apodization. Part I: Apodization Design and Line Element Beamformingcitations
- 20153-D Imaging Using Row–Column-Addressed Arrays With Integrated Apodization. Part I: Apodization Design and Line Element Beamformingcitations
- 20153-D Imaging Using Row-Column-Addressed Arrays With Integrated Apodization:Part II: Transducer Fabrication and Experimental Resultscitations
- 20153-D Imaging Using Row-Column-Addressed Arrays With Integrated Apodizationcitations
- 2012Multilayer piezoelectric transducer models combined with Field IIcitations
- 2011Performance Evaluation of a Synthetic Aperture Real-Time Ultrasound System
- 2010Simulation of High Quality Ultrasound Imaging
- 2009Parameter sensitivity study of a Field II multilayer transducer model on a convex transducercitations
- 2007Medical ultrasound imagingcitations
- 2004Preliminary In-Vivo Evaluation of Convex Array Synthetic Aperture Imagingcitations
- 2003Delay generation methods with reduced memory requirementscitations
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document
Real Time Synthetic Aperture and Plane Wave Ultrasound Imaging with the Xilinx VERSAL™ SIMD-VLIW Architecture
Abstract
A decade of technological improvement in SystemOn-Chip (SoC) integrated with Field Programmable Gate Arrays (FPGAs) have made it possible to successfully productize traditional ultrasound systems, especially portable ones. However, advanced modalities like Synthetic Aperture (SA) and Plane Wave (PW) Ultrafast imaging with their many advantages have not been targeted because of the sheer computing performance required for the ultrasound pipelines in real-time. Very large vector processers (DSPs and GPUs) solves some of the problems, but it runs into traditional scaling challenges due to inflexible, inefficient memory bandwidth usage and high-power consumption. Traditional FPGA solutions provide a programmable memory hierarchy, but the hardware development flow has been a barrier to broad, highvolume adoption. The need for low power and high performance must be explored beyond the conventional “one size fits all” CPU scalar processing solution for Ultrafast imaging to be a viable option. This paper presents a new technology called ‘Adaptive Compute Acceleration Platform’ (ACAP) on Xilinx’s Versal™ system, which has the capability of making real time SA and PW Ultrafast imaging possible.