Evidence map›Paper›PMID 40072764›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

Robotic CBCT meets robotic ultrasound.

Feng Li, Yuan Bi, Dianye Huang, Zhongliang Jiang, Nassir Navab

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. [Ultrasound technology's new application in the diagnosis and treatment of liver cancer].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026
    Review
  3. Review
  4. Article
  5. Ultrasound-guided real-time spinal motion visualization for spinal instability assessment.International journal of computer assisted radiology and surgery · 2026
    Article
  6. Article
  7. Review
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

5 authors.

Feng Li *CAMP, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0003-2717-8274
Yuan Bi *CAMP, Technical University of Munich, Munich, Germany.
Dianye HuangCAMP, Technical University of Munich, Munich, Germany.
Zhongliang JiangCAMP, Technical University of Munich, Munich, Germany. zl.jiang@tum.de.
Nassir NavabCAMP, Technical University of Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe multi-modality imaging system offers optimal fused images for safe and precise interventions in modern clinical practices, such as computed tomography-ultrasound (CT-US) guidance for needle insertion. However, the limited dexterity and mobility of current imaging devices hinder their integration into standardized workflows and the advancement toward fully autonomous intervention systems. In this paper, we present a novel clinical setup where robotic cone beam computed tomography (CBCT) and robotic US are pre-calibrated and dynamically co-registered, enabling new clinical applications. This setup allows registration-free rigid registration, facilitating multi-modal guided procedures in the absence of tissue deformation.

methodsFirst, a one-time pre-calibration is performed between the systems. To ensure a safe insertion path by highlighting critical vasculature on the 3D CBCT, SAM2 segments vessels from B-mode images, using the Doppler signal as an autonomously generated prompt. Based on the registration, the Doppler image or segmented vessel masks are then mapped onto the CBCT, creating an optimally fused image with comprehensive detail. To validate the system, we used a specially designed phantom, featuring lesions covered by ribs and multiple vessels with simulated moving flow.

resultsThe mapping error between US and CBCT resulted in an average deviation of

conclusionWe present the first robotic dual-modality imaging system designed to guide clinical applications. The results show significant performance improvements compared to traditional manual interventions.

Indexed as

Cone-Beam Computed TomographyMultimodal ImagingRoboticsRobotic Surgical ProceduresUltrasonography, InterventionalHumansImaging, Three-DimensionalPhantoms, ImagingUltrasonographyMultimodality fusionRobotic ultrasoundVisualization

Identifiers

PMID40072764
PMCPMC12167334

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Registered trials

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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.