Evidence map›Paper›PMID 41078859›Full record

ReviewMethodist DeBakey cardiovascular journal2025

The Fusion of Robotics and Imaging: A Vision of the Future.

Carlos Quintero-Peña, Austin R Shelton, Stuart J Corr, Alan B Lumsden

Abstract readReview
In one paragraph

Review in Methodist DeBakey cardiovascular journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Carlos Quintero-PeñaThe Bookout Center, Houston Methodist Academic Institute, Houston, Texas, US.ORCID https://orcid.org/0000-0003-0915-8691
Austin R SheltonThe Bookout Center, Houston Methodist Academic Institute, Houston, Texas, US.ORCID https://orcid.org/0009-0005-7619-0087
Stuart J CorrThe Bookout Center, Houston Methodist Academic Institute, Houston, Texas, US.ORCID https://orcid.org/0000-0002-9865-5309
Alan B LumsdenMethodist DeBakey Heart & Vascular Center, Houston Methodist, Houston, Texas, US.ORCID https://orcid.org/0009-0005-9620-5274

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical robotics has evolved significantly over the past decades, with more robotic systems than ever now in hospitals. The use of robots for surgery has already revolutionized the surgical landscape by providing high accuracy, greater surgeon dexterity, 3-dimensional visualization capabilities, and the potential for telesurgery. At the same time, diverse medical imaging modalities such as X-ray, computed tomography, magnetic resonance imaging, and ultrasound can provide meaningful visual information required for pre- and intraoperative planning and guidance, which is particularly important for robotic surgery given the surgeon's limited direct view of the surgical workspace in minimally invasive procedures. This review provides an overview of robotics technology for surgery and image acquisition and describes the main steps involved in the processing of medical imaging and its use. The authors also share their views on what the future of robotics and imaging may look like for surgical applications given the recent advances in artificial intelligence, computer vision, and machine learning.

Indexed as

Diagnostic ImagingMultimodal ImagingRobotic Surgical ProceduresSurgery, Computer-AssistedArtificial IntelligenceForecastingHumansImage Interpretation, Computer-AssistedMachine LearningPredictive Value of TestsSystems Integrationfuture trends in roboticsimage fusionrobotic surgery

Identifiers

PMID41078859
PMCPMC12513358

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.