Evidence map›Paper›PMID 32995981›Full record

ReviewInternational journal of computer assisted radiology and surgery2021

Enhancement of needle visualization and localization in ultrasound.

Parmida Beigi, Septimiu E Salcudean, Gary C Ng, Robert Rohling

Erratum issuedAbstract readReview
PubMed Publisher
In one paragraph

Review in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Needle tracking in low-resolution ultrasound volumes using deep learning.International journal of computer assisted radiology and surgery · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Enhancement of instrumented ultrasonic tracking images using deep learning.International journal of computer assisted radiology and surgery · 2023
    Article
  12. Article
  13. Review
  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Parmida BeigiElectrical and Computer Engineering Department, University of British Columbia, Vancouver, BC, Canada. parmidab@ece.ubc.ca.
Septimiu E SalcudeanElectrical and Computer Engineering Department, University of British Columbia, Vancouver, BC, Canada.
Gary C NgPhilips Ultrasound, Bothell, WA, USA.
Robert RohlingElectrical and Computer Engineering Department and Mechanical Engineering Department, University of British Columbia, Vancouver, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis scoping review covers needle visualization and localization techniques in ultrasound, where localization-based approaches mostly aim to compute the needle shaft (and tip) location while potentially enhancing its visibility too.

methodsA literature review is conducted on the state-of-the-art techniques, which could be divided into five categories: (1) signal and image processing-based techniques to augment the needle, (2) modifications to the needle and insertion to help with needle-transducer alignment and visibility, (3) changes to ultrasound image formation, (4) motion-based analysis and (5) machine learning.

resultsAdvantages, limitations and challenges of representative examples in each of the categories are discussed. Evaluation techniques performed in ex vivo, phantom and in vivo studies are discussed and summarized.

conclusionGreatest limitation of the majority of the literature is that they rely on original visibility of the needle in the static image. Need for additional/improved apparatus is the greatest limitation toward clinical utility in practice. SIGNIFICANCE: Ultrasound-guided needle placement is performed in many clinical applications, including biopsies, treatment injections and anesthesia. Despite the wide range and long history of this technique, an ongoing challenge is needle visibility in ultrasound. A robust technique to enhance ultrasonic needle visibility, especially for steeply inserted hand-held needles, and while maintaining clinical utility requirements is needed.

Indexed as

Image Processing, Computer-AssistedNeedlesBiopsyHumansMotionPhantoms, ImagingUltrasonography, InterventionalImage-guidanceImage processingMachine learningNeedle detectionNeedle visualizationUltrasound

Identifiers

What OpenQuestion holds

Textmetadata
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.