Evidence map›Paper›PMID 29796972›Full record

ArticleJournal of digital imaging2018

Three-Dimensional Surface Point Cloud Ultrasound for Better Understanding and Transmission of Ultrasound Scan Information.

Joseph Nathaniel Stember

Abstract read
In one paragraph

Article in Journal of digital imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Joseph Nathaniel StemberDepartment of Radiology, Columbia University Medical Center, 622 West 168th Street, PB 1-301, New York, NY, 10032, USA. jns2001@nyp.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound is notoriously plagued by high user dependence. There is a steep drop-off in information in going from what the sonographer sees during image acquisition and what the interpreting radiologist is able to view at the reading station. One countermeasure is probe localization and tracking. Current implementations are too difficult and expensive to use and/or do not provide adequate detail and perspective. The aim of this work was to demonstrate that a protocol combining surface three-dimensional photographic imaging with traditional ultrasound images may be a solution to the problem of probe localization, this approach being termed surface point cloud ultrasound (SPC-US). Ultrasound images were obtained of major vessels in an ultrasound training phantom, while simultaneously obtaining surface point cloud (SPC) 3D photographic images, with additional scanning performed on the right forearm soft tissues, kidneys, chest, and pelvis. The resulting sets of grayscale/color Doppler ultrasound and SPC images are juxtaposed and displayed for interpretation in a manner analogous to current text-based annotation or computer-generated stick figure probe position illustrations. Clearly demonstrated is that SPC-US better communicates information of probe position and orientation. Overall, it is shown that SPC-US provides much richer image representations of probe position on the patients than the current prevailing schemes. SPC-US turns out to be a rather general technique with many anticipated future applications, though only a few sample applications are illustrated in the present work.

Indexed as

AlgorithmsBlood VesselsEquipment DesignHumansImage Processing, Computer-AssistedImaging, Three-DimensionalPhantoms, ImagingUltrasonographyPoint cloudThree-dimensional cameraThree-dimensional surfaceUltrasound navigationUltrasound probe position

Identifiers

PMID29796972
PMCPMC6261187

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.