Evidence map›Paper›PMID 39301198›Full record

ArticleProceedings. IEEE International Symposium on Biomedical Imaging2024

Blood Harmonisation of Endoscopic Transsphenoidal Surgical Video Frames on Phantom Models.

Mahrukh Saeed, Julien Quarez, Hassna Irzan, Bava Kesavan, Matthew Elliot, Oscar Maccormac, James Knight, Sebastien Ourselin, Jonathan Shapey, Alejandro Granados

Abstract read
In one paragraph

Article in Proceedings. IEEE International Symposium on Biomedical Imaging, 2024. 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

10 authors.

Mahrukh SaeedSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Julien QuarezSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Hassna IrzanSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Bava KesavanSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Matthew ElliotSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Oscar MaccormacSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
James KnightNeurosurgery, King's College Hospital, London, UK.
Sebastien OurselinSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Jonathan ShapeySchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.
Alejandro GranadosSchool of Biomedical Engineering and Imaging Sciences, King's College London, UK.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Physical phantom models have been integral to surgical training, yet they lack realism and are unable to replicate the presence of blood resulting from surgical actions. Existing domain transfer methods aim to enhance realism, but none facilitate blood simulation. This study investigates the overlay of blood on images acquired during endoscopic transsphenoidal pituitary surgery on phantom models. The process involves employing manual techniques using the GIMP image manipulation application and automated methods using pythons Blend Modes module. We then approach this as an image harmonisation task to assess its practicality and feasibility. Our evaluation uses Structural Similarity Index Measure and Laplacian metrics. The results we obtained emphasize the significance of image harmonisation, offering substantial insights within the surgical field. Our work is a step towards investigating data-driven models that can simulate blood for increased realism during surgical training on phantom models.

Indexed as

blood simulationimage harmonisationphysical phantom modelssurgical trainingsurgical videos

Identifiers

PMID39301198
PMCPMC7616595

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.