Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next “Level”

Tirindelli, Maria Cristina; Victorova, Maria; Esteban, Javier; Kim, Seong Tae; Navarro-Alarcon, David; Zheng, Yongping; Navab, Nassir

doi:10.1109/lra.2020.3009069

Cited by 36 publications

(24 citation statements)

References 18 publications

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“…Production is the historical sector of robotics; applications include: manufacturing (assembly, welding, pick-and-place), transportation (autonomous guided vehicles, logistics) and construction (material and brick transfer). The medical category has become very popular in recent years, with applications spanning from robotic surgery (surgical grippers and needle manipulation), diagnosis (positioning of ultrasonic probes; Tirindelli et al, 2020 or endoscopes), and assistance (intelligent wheelchairs, feeding and walking aids). The service sector is the one that in the authors' opinion presents the highest potential for growth in the coming years.…”

Section: Classification Of Work and Discussionmentioning

confidence: 99%

Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

Cherubini

Navarro-Alarcon

2021

Front. Neurorobot.

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The objective of this paper is to present a systematic review of existing sensor-based control methodologies for applications that involve direct interaction between humans and robots, in the form of either physical collaboration or safe coexistence. To this end, we first introduce the basic formulation of the sensor-servo problem, and then, present its most common approaches: vision-based, touch-based, audio-based, and distance-based control. Afterwards, we discuss and formalize the methods that integrate heterogeneous sensors at the control level. The surveyed body of literature is classified according to various factors such as: sensor type, sensor integration method, and application domain. Finally, we discuss open problems, potential applications, and future research directions.

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Section: Classification Of Work and Discussionmentioning

confidence: 99%

Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

Cherubini

Navarro-Alarcon

2021

Front. Neurorobot.

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“…The path for the manual scanning was computed after the manual procedure was performed, while for robotic approach the path was used for the navigation purpose. The scanning settings were the following: speed of v = 0.004, velocity output clipping of v lim = 0.002, force setpoint F = 15N (the force range was chosen according to our previous work on spinal scanning [19]), PID control K p = 0.0003, K d = K i = 0.00003 and tilt coefficient K pitch = 0.07. Kalman filter parameters for spinous process location output were Q = 0.5, R = 500.…”

Section: Real-time Experiments Of Human Examination With Robotic-ultr...mentioning

confidence: 99%

Follow the Curve: Robotic-Ultrasound Navigation with Learning Based Localization of Spinous Processes for Scoliosis Assessment

Victorova¹,

Ka-Shing²,

Navarro-Alarcon³

et al. 2021

Preprint

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The scoliosis progression in adolescents requires close monitoring to timely take treatment measures. Ultrasound imaging is a radiation-free and low-cost alternative in scoliosis assessment to X-rays, which are typically used in clinical practice. However, ultrasound images are prone to speckle noises, making it challenging for sonographers to detect bony features and follow the spine's curvature. This paper introduces a robotic-ultrasound approach for spinal curvature tracking and automatic navigation. A fully connected network with deconvolutional heads is developed to locate the spinous process efficiently with real-time ultrasound images. We use this machine learning-based method to guide the motion of the robot-held ultrasound probe and follow the spinal curvature while capturing ultrasound images and correspondent position. We developed a new force-driven controller that automatically adjusts the probe's pose relative to the skin surface to ensure a good acoustic coupling between the probe and skin. After the scanning, the acquired data is used to reconstruct the coronal spinal image, where the deformity of the scoliosis spine can be assessed and measured. To evaluate the performance of our methodology, we conducted an experimental study with human subjects where the deviations from the image center during the robotized procedure are compared to that obtained from manual scanning. The angles of spinal deformity measured on spinal reconstruction images were similar for both methods, implying that they equally reflect human anatomy.

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“…Although efforts in telerobotic sonography have primarily focused on solutions that allow sonographers to remotely manipulate an ultrasound probe, development of autonomous ultrasound scanning, which is most established in the area of automated breast sonography, 54 is another area for further advancement. Analyzing force and ultrasound image data together in real time using deep learning, similar to that recently used for vertebral level localization, 55 may be a promising approach toward autonomous ultrasound scanning.…”

Section: Future Directionsmentioning

confidence: 99%

Telerobotic Sonography for Remote Diagnostic Imaging

Adams

Burbridge

Obaid

et al. 2020

J of Ultrasound Medicine

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Access to sonographers and sonologists is limited in many communities around the world. Telerobotic sonography (robotic ultrasound) is a new technology to increase access to sonography, providing sonographers and sonologists the ability to manipulate an ultrasound probe from a distant location and remotely perform ultrasound examinations. This narrative review discusses the development of telerobotic ultrasound systems, clinical studies evaluating the feasibility and diagnostic accuracy of telerobotic sonography, and emerging use of telerobotic sonography in clinical settings. Telerobotic sonography provides an opportunity to provide real‐time ultrasound examinations to underserviced rural and remote communities to increase equity in the delivery of diagnostic imaging.

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Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next “Level”

Cited by 36 publications

References 18 publications

Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

Sensor-Based Control for Collaborative Robots: Fundamentals, Challenges, and Opportunities

Follow the Curve: Robotic-Ultrasound Navigation with Learning Based Localization of Spinous Processes for Scoliosis Assessment

Telerobotic Sonography for Remote Diagnostic Imaging

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