Evidence map›Paper›PMID 27097600›Full record

ArticleInternational journal of computer assisted radiology and surgery2016

Dual-robot ultrasound-guided needle placement: closing the planning-imaging-action loop.

Risto Kojcev, Bernhard Fuerst, Oliver Zettinig, Javad Fotouhi, Sing Chun Lee, Benjamin Frisch, Russell Taylor, Edoardo Sinibaldi, Nassir Navab

Abstract read
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Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. AURA-CVC: Autonomous Ultrasound-guided Robotic Assistance for Central Venous Catheterization.International journal of computer assisted radiology and surgery · 2026
    Article
  2. Review
  3. Review
  4. Simple Frame-based Approach for MR Imaging-guided Abdominal Biopsy: Preliminary Evaluation in a Phantom Model.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026
    Article
  5. Review
  6. Article
  7. Respiration-Induced Organ Motion Compensation: A Review.Annals of biomedical engineering · 2025
    Review
  8. Article
  9. Review
  10. Article
  11. Automatic ultrasound scanning robotic system with optical waveguide-based force measurement.International journal of computer assisted radiology and surgery · 2021
    Article
  12. Ultrasound-guided needle insertion robotic system for percutaneous puncture.International journal of computer assisted radiology and surgery · 2021
    Article
  13. Article
  14. Design of an end-effector for robot-assisted ultrasound-guided breast biopsies.International journal of computer assisted radiology and surgery · 2020
    Article
  15. On the reproducibility of expert-operated and robotic ultrasound acquisitions.International journal of computer assisted radiology and surgery · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Risto KojcevComputer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA. risto.kojcev@iit.it.
Bernhard FuerstComputer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA.
Oliver ZettinigComputer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Javad FotouhiComputer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA.
Sing Chun LeeComputer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA.
Benjamin FrischComputer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Russell TaylorLaboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Edoardo SinibaldiCenter for Micro-BioRobotics, Istituto Italiano di Tecnologia, Pontedera, PI, Italy.
Nassir NavabComputer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePrecise needle placement is an important task during several medical procedures. Ultrasound imaging is often used to guide the needle toward the target region in soft tissue. This task remains challenging due to the user's dependence on image quality, limited field of view, moving target, and moving needle. In this paper, we present a novel dual-robot framework for robotic needle insertions under robotic ultrasound guidance.

methodWe integrated force-controlled ultrasound image acquisition, registration of preoperative and intraoperative images, vision-based robot control, and target localization, in combination with a novel needle tracking algorithm. The framework allows robotic needle insertion to target a preoperatively defined region of interest while enabling real-time visualization and adaptive trajectory planning to provide safe and quick interactions. We assessed the framework by considering both static and moving targets embedded in water and tissue-mimicking gelatin.

resultsThe presented dual-robot tracking algorithms allow for accurate needle placement, namely to target the region of interest with an error around 1 mm.

conclusionTo the best of our knowledge, we show the first use of two independent robots, one for imaging, the other for needle insertion, that are simultaneously controlled using image processing algorithms. Experimental results show the feasibility and demonstrate the accuracy and robustness of the process.

Indexed as

AlgorithmsEquipment DesignHumansImage Processing, Computer-AssistedNeedlesPhantoms, ImagingRobotic Surgical ProceduresSoftwareSoftware DesignSurgery, Computer-AssistedUltrasonographyInstrument and patient localization and trackingRobotic architecture and devicesRoboticsRobotic system and softwareSoftware architectureUltrasound

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.