Evidence map›Paper›PMID 39400852›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

Real-time ultrasound AR 3D visualization toward better topological structure perception for hepatobiliary surgery.

Yuqi Ji, Tianqi Huang, Yutong Wu, Ruiyang Li, Pengfei Wang, Jiahong Dong, Honegen Liao

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Observational
  4. Review
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.

Yuqi JiSchool of Biomedical Engineering, Tsinghua University, Beijing, China.
Tianqi HuangSchool of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
Yutong WuSchool of Biomedical Engineering, Tsinghua University, Beijing, China.
Ruiyang LiSchool of Biomedical Engineering, Tsinghua University, Beijing, China.
Pengfei WangHepatopancreatobiliary Center, Beijing Tsinghua Changgung Hospital, Beijing, China.
Jiahong DongSchool of ClinicalMedicine, Key Laboratory of Digital Intelligence, Hepatology (Ministry of Education), Tsinghua University, Beijing, China. dongjiahong@mail.tsinghua.edu.cn.
Honegen LiaoSchool of Biomedical Engineering, Tsinghua University, Beijing, China. liao@tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-3847-9347

Funding

CAMS Innovation Fund for Medical Sciences 2019-12M-5056Chongqing Municipal Key Research and Development Program of China 2022YFC2405200Institute for Intelligent Healthcare, Tsinghua University 2022ZLB001National Natural Science Foundation of China 62101305National Natural Science Foundation of China 81930119National Natural Science Foundation of China 82027807National Natural Science Foundation of China U22A2051Tsinghua-Foshan Innovation Special Fund 2021THFS0104
6 · The paper itself

Abstract

purposeUltrasound serves as a crucial intraoperative imaging tool for hepatobiliary surgeons, enabling the identification of complex anatomical structures like blood vessels, bile ducts, and lesions. However, the reliance on manual mental reconstruction of 3D topologies from 2D ultrasound images presents significant challenges, leading to a pressing need for tools to assist surgeons with real-time identification of 3D topological anatomy.

methodsWe propose a real-time ultrasound AR 3D visualization method for intraoperative 2D ultrasound imaging. Our system leverages backward alpha blending to integrate multi-planar ultrasound data effectively. To ensure continuity between 2D ultrasound planes, we employ spatial smoothing techniques to interpolate the widely spaced ultrasound planes. A dynamic 3D transfer function is also developed to enhance spatial representation through color differentiation.

resultsComparative experiments involving our AR visualization of 3D ultrasound, alongside AR visualization of 2D ultrasound and 2D visualization of 3D ultrasound, demonstrated that the proposed method significantly reduced operational time(110.25 ± 27.83 s compared to 292 ± 146.63 s and 365.25 ± 131.62 s), improved depth perception and comprehension of complex topologies, contributing to reduced pressure and increased personal satisfaction among users.

conclusionQuantitative experimental results and feedback from both novice and experienced physicians highlight our system's exceptional ability to enhance the understanding of complex topological anatomy. This improvement is crucial for accurate ultrasound diagnosis and informed surgical decision-making, underscoring the system's clinical applicability.

Indexed as

Augmented RealityImaging, Three-DimensionalSurgery, Computer-AssistedHumansLiverUltrasonography3D renderingAugmented realityHepatobiliary surgeryUltrasound

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.