A-SEE: Active-Sensing End-effector Enabled Probe Self-Normal-Positioning for Robotic Ultrasound Imaging Applications

Large area kidney imaging for pre-transplant evaluation using real-time robotic optical coherence tomography

Optical coherence tomography (OCT) can be used to image microstructures of human kidneys. However, current OCT probes exhibit inadequate field-of-view, leading to potentially biased kidney assessment. Here we present a robotic OCT system where the probe is integrated to a robot manipulator, enabling wider area (covers an area of 106.39 mm by 37.70 mm) spatially-resolved imaging. Our system comprehensively scans the kidney surface at the optimal altitude with preoperative path planning and OCT image-based feedback control scheme. It further parameterizes and visualizes microstructures of large area. We verified the system positioning accuracy on a phantom as 0.0762 ± 0.0727 mm and showed the clinical feasibility by scanning ex vivo kidneys. The parameterization reveals vasculatures beneath the kidney surface. Quantification on the proximal convoluted tubule of a human kidney yields clinical-relevant information. The system promises to assess kidney viability for transplantation after collecting a vast amount of whole-organ parameterization and patient outcomes data.

A review of robot-assisted ultrasound examination: Systems and technology

BACKGROUND

At present, the number and overall level of ultrasound (US) doctors cannot meet the medical needs, and the medical ultrasound robots will largely solve the shortage of medical resources.

METHODS

According to the degree of automation, the handheld, semi-automatic and automatic ultrasound examination robot systems are summarised. Ultrasound scanning path planning and robot control are the keys to ensure that the robot systems can obtain high-quality images. Therefore, the ultrasound scanning path planning and control methods are summarised. The research progress and future trends are discussed.

RESULTS

A variety of ultrasound robot systems have been applied to various medical works. With the continuous improvement of automation, the systems provide high-quality ultrasound images and image guidance for clinicians.

CONCLUSION

Although the development of medical ultrasound robot still faces challenges, with the continuous progress of robot technology and communication technology, medical ultrasound robot will have great development potential and broad application space.

Robotic ultrasound imaging: State-of-the-art and future perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques. Additionally, we present the challenges that the scientific community needs to face in the coming years in order to achieve its ultimate goal of developing intelligent robotic sonographer colleagues. These colleagues are expected to be capable of collaborating with human sonographers in dynamic environments to enhance both diagnostic and intraoperative imaging.

Intraoperative laparoscopic photoacoustic image guidance system in the da Vinci surgical system

This paper describes a framework allowing intraoperative photoacoustic (PA) imaging integrated into minimally invasive surgical systems. PA is an emerging imaging modality that combines the high penetration of ultrasound (US) imaging with high optical contrast. With PA imaging, a surgical robot can provide intraoperative neurovascular guidance to the operating physician, alerting them of the presence of vital substrate anatomy invisible to the naked eye, preventing complications such as hemorrhage and paralysis. Our proposed framework is designed to work with the da Vinci surgical system: real-time PA images produced by the framework are superimposed on the endoscopic video feed with an augmented reality overlay, thus enabling intuitive three-dimensional localization of critical anatomy. To evaluate the accuracy of the proposed framework, we first conducted experimental studies in a phantom with known geometry, which revealed a volumetric reconstruction error of 1.20 ± 0.71 mm. We also conducted an ex vivo study by embedding blood-filled tubes into chicken breast, demonstrating the successful real-time PA-augmented vessel visualization onto the endoscopic view. These results suggest that the proposed framework could provide anatomical and functional feedback to surgeons and it has the potential to be incorporated into robot-assisted minimally invasive surgical procedures.