Evidence map›Paper›PMID 38786574›Full record

ReviewJournal of imaging2024

Advances in Real-Time 3D Reconstruction for Medical Endoscopy.

Alexander Richter, Till Steinmann, Jean-Claude Rosenthal, Stefan J Rupitsch

Abstract readReview
In one paragraph

Review in Journal of imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Neural Radiance Fields (NeRF) for 3D Reconstruction of Monocular Endoscopic Video in Sinus Surgery.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2025
    Article
  8. 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

4 authors.

Alexander RichterFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut (EMI), Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.ORCID 0000-0002-9413-9083
Till SteinmannElectrical Instrumentation and Embedded Systems, Albert-Ludwigs-Universität Freiburg, Goerges-Köhler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0002-0890-5184
Jean-Claude RosenthalFraunhofer Institute for Telecommunications, Heinrich-Hertz-Institut (HHI), Einsteinufer 37, 10587 Berlin, Germany.ORCID 0000-0002-8069-2558
Stefan J RupitschElectrical Instrumentation and Embedded Systems, Albert-Ludwigs-Universität Freiburg, Goerges-Köhler-Allee 106, 79110 Freiburg, Germany.ORCID 0000-0002-4806-9838

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This contribution is intended to provide researchers with a comprehensive overview of the current state-of-the-art concerning real-time 3D reconstruction methods suitable for medical endoscopy. Over the past decade, there have been various technological advancements in computational power and an increased research effort in many computer vision fields such as autonomous driving, robotics, and unmanned aerial vehicles. Some of these advancements can also be adapted to the field of medical endoscopy while coping with challenges such as featureless surfaces, varying lighting conditions, and deformable structures. To provide a comprehensive overview, a logical division of monocular, binocular, trinocular, and multiocular methods is performed and also active and passive methods are distinguished. Within these categories, we consider both flexible and non-flexible endoscopes to cover the state-of-the-art as fully as possible. The relevant error metrics to compare the publications presented here are discussed, and the choice of when to choose a GPU rather than an FPGA for camera-based 3D reconstruction is debated. We elaborate on the good practice of using datasets and provide a direct comparison of the presented work. It is important to note that in addition to medical publications, publications evaluated on the KITTI and Middlebury datasets are also considered to include related methods that may be suited for medical 3D reconstruction.

Indexed as

computer visionmedical endoscopyminimally invasive surgeryreal-time 3D reconstruction

Identifiers

PMID38786574
PMCPMC11122342

What OpenQuestion 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 OpenQuestion graph.