Evidence map›Paper›PMID 40824333›Full record

ArticlePhysical and engineering sciences in medicine2025

Advanced fiber optic systems for efficient medical image transmission: a telemedicine perspective.

Bengana Abdelfatih, Debbal Mohammed, Bouregaa Moueffeq, Bemmoussat Chemseddine

Abstract read
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Article in Physical and engineering sciences in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Bengana AbdelfatihDepartment of Biomedical Engineering, Faculty of Technology, Laboratory of Biomedical Engineering, University of Tlemcen, Tlemcen, Algeria.
Debbal MohammedDepartment of Electronics and Telecommunications, University of Ain Témouchent, Ain Témouchent, Algeria. mohammed.debbal@univ-temouchent.edu.dz.ORCID http://orcid.org/0000-0002-7018-5624
Bouregaa MoueffeqDepartment of Electrical Engineering, University of Mustapha Stambouli, Mascara, Algeria.
Bemmoussat ChemseddineDepartment of Electronics and Telecommunications, University of Ain Témouchent, Ain Témouchent, Algeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing demand for secure, high-quality medical image transmission across healthcare institutions has posed a significant challenge to modern telemedicine systems. Traditional network infrastructures often fail to provide sufficient bandwidth and low latency required for transferring large volumes of high-resolution medical images, such as MRI and CT scans, over long distances. To address this limitation, a fiber-optic transmission framework was designed and evaluated with the objective of enhancing the speed, reliability, and accuracy of inter-hospital medical image sharing. In this study, a simulation-based approach was employed using OPTISYSTEM and MATLAB to model the optical transmission chain, including stages of image digitization, modulation, fiber propagation, and optical-to-electrical conversion at the receiving end. Various performance parameters such as Bit Error Rate (BER), Quality Factor (Q), transmission power, and noise levels were analyzed for different image resolutions and transmission distances. The results showed that Q-Factor values between 8.5 and 9.5 were obtained, with BER reaching values as low as 10⁻

Indexed as

Diagnostic ImagingFiber Optic TechnologyOptical FibersTelemedicineHumansImage Processing, Computer-AssistedBit error rate (BER)Fiber-optic networksMedical image transmissionOptical communication systemsQuality factor (Q)Telemedicine

Identifiers

PMID40824333

What OpenQuestion holds

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Registered trials

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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.