Towards Autonomous Robotic Kidney Ultrasound: Spatial-Efficient Volumetric Imaging via Template Guided Optimal Pivoting

2026-02-18

AI Summary

This work proposes an autonomous robotic workflow for renal ultrasound imaging that addresses the limitations of conventional handheld approaches—such as operator dependence, incomplete coverage, and lack of volumetric localization—and overcomes the inefficiencies of existing robotic methods that struggle to identify optimal imaging windows, often resulting in redundant scans. The system performs an initial exploratory scan to acquire partial kidney observations, registers them to an anatomical template to estimate organ pose, and then guides the probe to pivot around a fixed fulcrum while sweeping along the renal longitudinal axis, thereby minimizing translational motion. By integrating anatomical template guidance with a fulcrum-constrained optimal sweeping strategy, the method significantly reduces probe footprint while enhancing spatial coverage and efficiency. Simulations indicate that 60% exploration suffices for balanced accuracy and efficiency, and in vivo experiments on two subjects achieved mean localization errors of 7.36 mm and 13.84°, with probe travel distance reduced by approximately 75 mm compared to baseline.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Medical ultrasound (US) imaging is a frontline tool for the diagnosis of kidney diseases. However, traditional freehand imaging procedure suffers from inconsistent, operator-dependent outcomes, lack of 3D localization information, and risks of work-related musculoskeletal disorders. While robotic ultrasound (RUS) systems offer the potential for standardized, operator-independent 3D kidney data acquisition, the existing scanning methods lack the ability to determine the optimal imaging window for efficient imaging. As a result, the scan is often blindly performed with excessive probe footprint, which frequently leads to acoustic shadowing and incomplete organ coverage. Consequently, there is a critical need for a spatially efficient imaging technique that can maximize the kidney coverage through minimum probe footprint. Here, we propose an autonomous workflow to achieve efficient kidney imaging via template-guided optimal pivoting. The system first performs an explorative imaging to generate partial observations of the kidney. This data is then registered to a kidney template to estimate the organ pose. With the kidney localized, the robot executes a fixed-point pivoting sweep where the imaging plane is aligned with the kidney long axis to minimize the probe translation. The proposed method was validated in simulation and in-vivo. Simulation results indicate that a 60% exploration ratio provides optimal balance between kidney localization accuracy and scanning efficiency. In-vivo evaluation on two male subjects demonstrates a kidney localization accuracy up to 7.36 mm and 13.84 degrees. Moreover, the optimal pivoting approach shortened the probe footprint by around 75 mm when compared with the baselines. These results valid our approach of leveraging anatomical templates to align the probe optimally for volumetric sweep.

Problem

• robotic ultrasound
• kidney imaging
• spatial-efficient scanning
• optimal imaging window
• volumetric ultrasound

Innovation

• template-guided pivoting
• robotic ultrasound
• spatial-efficient imaging
• kidney localization
• volumetric sweep