Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model

These findings emphasize the model's ability to effectively diagnose retinal disorders using OCT images and indicate substantial promise for the development of computer-aided diagnostic tools in the field of ophthalmology.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-02-07
DOI
https://doi.org/10.1371/journal.pone.0318657
Citations
12
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
16.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model

Gülcan Gencer, Kerem Gencer
12 citations
PLoS ONE
Retinal Imaging and Analysis
16.32
article

Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model

Gülcan Gencer, Kerem Gencer
article en
12 citations

Abstract

These findings emphasize the model's ability to effectively diagnose retinal disorders using OCT images and indicate substantial promise for the development of computer-aided diagnostic tools in the field of ophthalmology.

PLoS ONEVol. 20(2)
Afyonkarahisar Sağlık Bilimleri Üniversitesi, Afyon Kocatepe University (TR)
Openalex Percentile: Top 1%
Retinal Imaging and Analysis
16.32
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model — Gülcan Gencer, Kerem Gencer · PLoS ONE (2025) | TGRS Research Map | TGRS