Ultrasound Beamforming: Exploring Cloud-Native and Edge Computing Solution

Ultrasound imaging is pivotal in modern medicine for its non-invasive visualization of anatomical structures. How- ever, traditional systems face challenges in scalability, flexibility, and cost-effectiveness due to centralized processing units. This paper introduces a novel cloud-native architecture tailored for ultrasound imaging, focusing on the computationally intensive beamforming process. The architecture integrates on-premise edge-computing acquisition probes with cloud-based processing, leveraging edge computing to enhance efficiency and responsive- ness. Initial data preprocessing at the edge optimizes bandwidth use before secure transmission to the cloud via dedicated connections. In the cloud, real-time data ingestion through AWS Kinesis supports scalable processing using containerization technologies. High-performance computing languages ensure efficient beam- forming, improving diagnostic accuracy and operational efficacy. The architecture's scalability, cost-effectiveness, and integration potential for AI-driven diagnostics are discussed, highlighting its transformative impact on ultrasound imaging practices and healthcare delivery.

Authors

Institutions

Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/ictacs62700.2024.10841187
Citations
2
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
0.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ultrasound Beamforming: Exploring Cloud-Native and Edge Computing Solution

Mohamed Sadik, Hamza Hadri, Abderahhim Fail, Amine Essaken
2 citations
Robotics and Automated Systems
0.66
article

Ultrasound Beamforming: Exploring Cloud-Native and Edge Computing Solution

Mohamed Sadik, Hamza Hadri, Abderahhim Fail, Amine Essaken
article en
2 citations

Abstract

Ultrasound imaging is pivotal in modern medicine for its non-invasive visualization of anatomical structures. How- ever, traditional systems face challenges in scalability, flexibility, and cost-effectiveness due to centralized processing units. This paper introduces a novel cloud-native architecture tailored for ultrasound imaging, focusing on the computationally intensive beamforming process. The architecture integrates on-premise edge-computing acquisition probes with cloud-based processing, leveraging edge computing to enhance efficiency and responsive- ness. Initial data preprocessing at the edge optimizes bandwidth use before secure transmission to the cloud via dedicated connections. In the cloud, real-time data ingestion through AWS Kinesis supports scalable processing using containerization technologies. High-performance computing languages ensure efficient beam- forming, improving diagnostic accuracy and operational efficacy. The architecture's scalability, cost-effectiveness, and integration potential for AI-driven diagnostics are discussed, highlighting its transformative impact on ultrasound imaging practices and healthcare delivery.

University of Hassan II Casablanca (MA)
Openalex Percentile: Top 27%
Robotics and Automated Systems
0.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.