# Machine Learning in Robotic Ultrasound Imaging: Challenges and Perspectives

arXiv: https://arxiv.org/abs/2401.02376 · HTML: https://mlsanity.com/paper/2401.02376/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jan 2024.

## Built on by (most cited first, 17 of 17)

- [From Screens to Scenes: A Survey of Embodied AI in Healthcare](https://mlsanity.com/paper/2501.07468/) (2025)
- [Speckle2Self: Self-Supervised Ultrasound Speckle Reduction Without Clean Data](https://mlsanity.com/paper/2507.06828/) (2025)
- [VibNet: Vibration-Boosted Needle Detection in Ultrasound Images](https://mlsanity.com/paper/2403.14523/) (2024)
- [Class-Aware Cartilage Segmentation for Autonomous US-CT Registration in Robotic Intercostal Ultrasound Imaging](https://mlsanity.com/paper/2406.04100/) (2024)
- [LOOC: Localizing Organs using Occupancy Networks and Body Surface Depth Images](https://mlsanity.com/paper/2406.12407/) (2024)
- [UltraAD: Fine-Grained Ultrasound Anomaly Classification via Few-Shot CLIP Adaptation](https://mlsanity.com/paper/2506.19694/) (2025)
- [Autonomous Path Planning for Intercostal Robotic Ultrasound Imaging Using Reinforcement Learning](https://mlsanity.com/paper/2404.09927/) (2024)
- [Comprehensive Review of Reinforcement Learning for Medical Ultrasound Imaging](https://mlsanity.com/paper/2503.16543/) (2025)
- [Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment](https://mlsanity.com/paper/2602.12917/) (2026)
- [Echo-POSED: Geometric Self-Distillation for Echocardiography Guidance](https://mlsanity.com/paper/2606.02634/) (2026)
- [Vibration-Based Energy Metric for Restoring Needle Alignment in Autonomous Robotic Ultrasound](https://mlsanity.com/paper/2508.06921/) (2025)
- [ConVibNet: Needle Detection during Continuous Insertion via Frequency-Inspired Features](https://mlsanity.com/paper/2603.01147/) (2026)
- [Robotic Ultrasound Makes CBCT Alive](https://mlsanity.com/paper/2603.10220/) (2026)
- [Anatomical Prior-Driven Framework for Autonomous Robotic Cardiac Ultrasound Standard View Acquisition](https://mlsanity.com/paper/2603.21134/) (2026)
- [UltraG-Ray: Physics-Based Gaussian Ray Casting for Novel Ultrasound View Synthesis](https://mlsanity.com/paper/2603.29022/) (2026)
- [SAMe: A Semantic Anatomy Mapping Engine for Robotic Ultrasound](https://mlsanity.com/paper/2604.25646/) (2026)
- [Scanning While Imagining: A Scene-Graph World Model for Robotic Ultrasound Navigation](https://mlsanity.com/paper/2609.32837/) (2026)

## Abstract (arXiv)

This article reviews the recent advances in intelligent robotic ultrasound (US) imaging systems. We commence by presenting the commonly employed robotic mechanisms and control techniques in robotic US imaging, along with their clinical applications. Subsequently, we focus on the deployment of machine learning techniques in the development of robotic sonographers, emphasizing crucial developments aimed at enhancing the intelligence of these systems. The methods for achieving autonomous action reasoning are categorized into two sets of approaches: those relying on implicit environmental data interpretation and those using explicit interpretation. Throughout this exploration, we also discuss practical challenges, including those related to the scarcity of medical data, the need for a deeper understanding of the physical aspects involved, and effective data representation approaches. Moreover, we conclude by highlighting the open problems in the field and analyzing different possible perspectives on how the community could move forward in this research area.