Evidence map›Paper›PMID 37555199›Full record

ArticleComputer methods in biomechanics and biomedical engineering. Imaging & visualization2023

Mixed Reality Interfaces for Achieving Desired Views with Robotic X-ray Systems.

Benjamin D Killeen, Jonas Winter, Wenhao Gu, Alejandro Martin-Gomez, Russell H Taylor, Greg Osgood, Mathias Unberath

Abstract read
In one paragraph

Article in Computer methods in biomechanics and biomedical engineering. Imaging & visualization, 2023. 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. Pelphix: Surgical Phase Recognition from X-ray Images in Percutaneous Pelvic Fixation.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023
    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

7 authors.

Benjamin D KilleenLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Jonas WinterLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Wenhao GuLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Alejandro Martin-GomezLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Russell H TaylorLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Greg OsgoodDepartment of Orthopaedic Surgery, Johns Hopkins Hospital, Baltimore, MD, USA.
Mathias UnberathLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.

Funding

Task-aware and Autonomous Robotic C-arm Servoing for Flouroscopy-guided InterventionsR21EB028505 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI UNBERATH, MATHIAS · 2020 to 2022
$629k
NIBIB NIH HHS R21 EB028505
6 · The paper itself

Abstract

Robotic X-ray C-arm imaging systems can precisely achieve any position and orientation relative to the patient. Informing the system, however, what pose exactly corresponds to a desired view is challenging. Currently these systems are operated by the surgeon using joysticks, but this interaction paradigm is not necessarily effective because users may be unable to efficiently actuate more than a single axis of the system simultaneously. Moreover, novel robotic imaging systems, such as the Brainlab Loop-X, allow for independent source and detector movements, adding even more complexity. To address this challenge, we consider complementary interfaces for the surgeon to command robotic X-ray systems effectively. Specifically, we consider three interaction paradigms: (1) the use of a pointer to specify the principal ray of the desired view relative to the anatomy, (2) the same pointer, but combined with a mixed reality environment to synchronously render digitally reconstructed radiographs from the tool's pose, and (3) the same mixed reality environment but with a virtual X-ray source instead of the pointer. Initial human-in-the-loop evaluation with an attending trauma surgeon indicates that mixed reality interfaces for robotic X-ray system control are promising and may contribute to substantially reducing the number of X-ray images acquired solely during "fluoro hunting" for the desired view or standard plane.

Indexed as

C-arm positioningmixed realityX-ray

Identifiers

PMID37555199
PMCPMC10406465

What OpenQuestion holds

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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.