Evidence map›Paper›PMID 37153690›Full record

ArticleProceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems2022

A Metric for Finding Robust Start Positions for Medical Steerable Needle Automation.

Janine Hoelscher, Inbar Fried, Mengyu Fu, Mihir Patwardhan, Max Christman, Jason Akulian, Robert J Webster, Ron Alterovitz

Abstract read
In one paragraph

Article in Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022. 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. Safe Start Regions for Medical Steerable Needle Automation.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2025
    Article
  2. Landmark Based Bronchoscope Localization for Needle Insertion Under Respiratory Deformation.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2023
    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

8 authors.

Janine HoelscherDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Inbar FriedDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mengyu FuDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mihir PatwardhanDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Max ChristmanDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Jason AkulianDivision of Pulmonary Diseases and Critical Care Medicine at the University of North Carolina at Chapel Hill, NC 27599, USA.
Robert J WebsterDepartment of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Ron AlterovitzDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

Funding

Bronchoscopic Steerable Needles for Transparenchymal Access to Lung NodulesR01EB024864 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ALTEROVITZ, RON · 2017 to 2021
$2.5M
NIBIB NIH HHS R01 EB024864
6 · The paper itself

Abstract

Steerable needles are medical devices with the ability to follow curvilinear paths to reach targets while circumventing obstacles. In the deployment process, a human operator typically places the steerable needle at its start position on a tissue surface and then hands off control to the automation that steers the needle to the target. Due to uncertainty in the placement of the needle by the human operator, choosing a start position that is robust to deviations is crucial since some start positions may make it impossible for the steerable needle to safely reach the target. We introduce a method to efficiently evaluate steerable needle motion plans such that they are safe to variation in the start position. This method can be applied to many steerable needle planners and requires that the needle's orientation angle at insertion can be robotically controlled. Specifically, we introduce a method that builds a funnel around a given plan to determine a safe insertion surface corresponding to insertion points from which it is guaranteed that a collision-free motion plan to the goal can be computed. We use this technique to evaluate multiple feasible plans and select the one that maximizes the size of the safe insertion surface. We evaluate our method through simulation in a lung biopsy scenario and show that the method is able to quickly find needle plans with a large safe insertion surface.

Identifiers

PMID37153690
PMCPMC10162587

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.