Evidence map›Paper›PMID 38139718›Full record

ReviewSensors (Basel, Switzerland)2023

Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization.

Zhefan Lin, Chen Lei, Liangjing Yang

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. CRAC-DM: class relation-aware categorical diffusion model for surgical scene segmentation.International journal of computer assisted radiology and surgery · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Assessment of cognitive load in the context of neurosurgery.International journal of computer assisted radiology and surgery · 2025
    Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Review
  14. The Fusion of Robotics and Imaging: A Vision of the Future.Methodist DeBakey cardiovascular journal · 2025
    Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. 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

3 authors.

Zhefan LinSchool of Mechanical Engineering, Zhejiang University, Hangzhou 310030, China.ORCID 0009-0003-3877-4634
Chen LeiZJU-UIUC Institute, International Campus, Zhejiang University, Haining 314400, China.
Liangjing YangSchool of Mechanical Engineering, Zhejiang University, Hangzhou 310030, China.ORCID 0000-0002-3294-0879

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical image analysis forms the basis of image-guided surgery (IGS) and many of its fundamental tasks. Driven by the growing number of medical imaging modalities, the research community of medical imaging has developed methods and achieved functionality breakthroughs. However, with the overwhelming pool of information in the literature, it has become increasingly challenging for researchers to extract context-relevant information for specific applications, especially when many widely used methods exist in a variety of versions optimized for their respective application domains. By being further equipped with sophisticated three-dimensional (3D) medical image visualization and digital reality technology, medical experts could enhance their performance capabilities in IGS by multiple folds. The goal of this narrative review is to organize the key components of IGS in the aspects of medical image processing and visualization with a new perspective and insights. The literature search was conducted using mainstream academic search engines with a combination of keywords relevant to the field up until mid-2022. This survey systemically summarizes the basic, mainstream, and state-of-the-art medical image processing methods as well as how visualization technology like augmented/mixed/virtual reality (AR/MR/VR) are enhancing performance in IGS. Further, we hope that this survey will shed some light on the future of IGS in the face of challenges and opportunities for the research directions of medical image processing and visualization.

Indexed as

Augmented RealitySurgery, Computer-AssistedVirtual RealityImage Processing, Computer-Assisted3D visual interfaceaugmented/mixed/virtual realityimage-guided surgerymedical image processingsurgical navigation

Identifiers

PMID38139718
PMCPMC10748263

What Socratic holds

Textmetadata
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 Socratic graph.