Evidence map›Paper›PMID 41007151›Full record

ReviewBioengineering (Basel, Switzerland)2025

Review of Linear-Array-Transducer-Based Volumetric Ultrasound Imaging Techniques and Their Biomedical Applications.

Ninjbadgar Tsedendamba, Yuon Song, Eun-Yeong Park, Jeesu Kim

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 3D Imaging and Measurement of Optic Nerve Sheath Diameter.Translational vision science & technology · 2026
    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.

Ninjbadgar TsedendambaDepartments of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
Yuon SongDepartments of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.ORCID 0009-0005-5946-9852
Eun-Yeong ParkDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea.ORCID 0000-0002-8643-3274
Jeesu KimDepartments of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.ORCID 0000-0002-2542-0234

Funding

The Korea Health Industry Development Institute (KHIDI) grant HR20C0026The National Research Foundation of Korea (NRF) grant RS-2021-NR060086, RS-2024-00427153
6 · The paper itself

Abstract

Ultrasound imaging is one of the most widespread biomedical imaging techniques thanks to its advantages such as being non-invasive, portable, non-ionizing, and cost-effective. Ultrasound imaging generally provides two-dimensional cross-sectional images, but the quality and interpretative ability vary based on the experience of the examiner, leading to a lack of objectivity and accuracy. To address these issues, there is a growing demand for three-dimensional ultrasound imaging. Among the various types of transducers used to obtain three-dimensional ultrasound images, this paper focuses on the most standardized probe, the linear array transducer, and provides an overview of the system implementations, imaging results, and applications of volumetric ultrasound imaging from the perspective of scanning methods. Through this comprehensive review, future researchers will gain insights into the advantages and disadvantages of various approaches to three-dimensional imaging systems using linear arrays, providing direction and applicability for system configuration and application.

Indexed as

biomedical imaginglinear-arrayultrasoundvolumetric imaging

Identifiers

PMID41007151
PMCPMC12467595

What OpenQuestion holds

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LicenceCC BY
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.