AI-Powered Robotic Ultrasound: Electronic Hardware, Algorithms, and Applications

Robotic ultrasound powered by Artificial Intelligence (AI) represents a groundbreaking and transformative innovation in the field of medical imaging. By seamlessly automating probe movement and using sophisticated algorithms, these systems enhance overall diagnostic accuracy and reduce considerably operator variability. This paper provides a comprehensive review of AI-based solutions for the development of robotic ultrasound systems, with a special focus on both Machine Learning (ML) and Deep Learning (DL) techniques. In particular, key areas of investigation include probe management strategies and image quality optimization approaches. Applications across various anatomical regions and diverse clinical scenarios demonstrate improved image quality and reduced operator workload, thereby contributing to more consistent and reliable diagnostic outcomes. Main robotic arms employed in these systems are also reviewed, with detailed analysis highlighting technical advancements and engineering innovations. The review underscores the growing role of AI in enhancing diagnostic procedures and supports its potential to revolutionize ultrasound practices, discussing in depth technical and practical challenges related to the implementation of these systems. Overall, the findings emphasize the transformative impact of integrating AI with robotic platforms.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3605105
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
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article

AI-Powered Robotic Ultrasound: Electronic Hardware, Algorithms, and Applications

Francesco Dell’Olio, Emanuele De Luca
IEEE Access
Medical Imaging and Analysis
article

AI-Powered Robotic Ultrasound: Electronic Hardware, Algorithms, and Applications

Francesco Dell’Olio, Emanuele De Luca
article en

Abstract

Robotic ultrasound powered by Artificial Intelligence (AI) represents a groundbreaking and transformative innovation in the field of medical imaging. By seamlessly automating probe movement and using sophisticated algorithms, these systems enhance overall diagnostic accuracy and reduce considerably operator variability. This paper provides a comprehensive review of AI-based solutions for the development of robotic ultrasound systems, with a special focus on both Machine Learning (ML) and Deep Learning (DL) techniques. In particular, key areas of investigation include probe management strategies and image quality optimization approaches. Applications across various anatomical regions and diverse clinical scenarios demonstrate improved image quality and reduced operator workload, thereby contributing to more consistent and reliable diagnostic outcomes. Main robotic arms employed in these systems are also reviewed, with detailed analysis highlighting technical advancements and engineering innovations. The review underscores the growing role of AI in enhancing diagnostic procedures and supports its potential to revolutionize ultrasound practices, discussing in depth technical and practical challenges related to the implementation of these systems. Overall, the findings emphasize the transformative impact of integrating AI with robotic platforms.

IEEE AccessVol. 13
Polytechnic University of Bari (IT)
Openalex Percentile: Top 78%
Medical Imaging and Analysis
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AI-Powered Robotic Ultrasound: Electronic Hardware, Algorithms, and Applications — Francesco Dell’Olio, Emanuele De Luca · IEEE Access (2025) | TGRS Research Map | TGRS