Leveraging ResNet50 With Swin Attention for Accurate Detection of OCT Biomarkers Using Fundus Images

IF 3.4 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Access Pub Date : 2025-02-21 DOI:10.1109/ACCESS.2025.3544332

S. Tamilselvi;M. Suchetha;Rajiv Raman

{"title":"Leveraging ResNet50 With Swin Attention for Accurate Detection of OCT Biomarkers Using Fundus Images","authors":"S. Tamilselvi;M. Suchetha;Rajiv Raman","doi":"10.1109/ACCESS.2025.3544332","DOIUrl":null,"url":null,"abstract":"Diabetes can impact the retina and cause a decline in vision for patients as a result of Diabetic Retinopathy (DR). Diabetic Macular Edema (DME) is a complication that results from the chronic damage to the tiny blood vessels of the retina that arises in the non-proliferative stage of DR (NPDR) but can also be present in proliferative DR (PDR) and potentially leading to vision loss. The duration of diabetes in patients affects both the prevalence and incidence of macular edema, as well as the progression of retinopathy. Therefore, regular screening of diabetes patients for the early detection of retinal abnormalities is essential to prevent the development and progression of DR and DME. The proposed model predicts DME-associated biomarkers, typically identified in Optical Coherence Tomography (OCT), using 2D fundus images. These biomarkers include center-involved diabetic macular edema (ci-DME), neurosensory detachment (NSD), Intraretinal fluid (IRF), disorganization of the retinal inner layers (DRIL), hyperreflective foci (HRF), and disruptions in the inner segment/outer segment (IS/OS) junction, utilizing 2D fundus images. The model integrates the feature extraction capability of ResNet50 with the spatial structural domain knowledge provided by the Swin attention augmentation layer. 2D fundus image datasets were collected to train and evaluate the model. In two distinct datasets, the model achieved a validation accuracy of 85.7% (95% CI: 81.6–90.6%) and 89.5% (95% CI: 85.6–93.4%), Cohen’s Kappa of 0.68 (95% CI: 0.61–0.77) and 0.75 (95% CI: 0.67–0.82), sensitivity of 88.6% (95% CI: 85.6–92.1%) and 79.6% (95% CI: 70.6–85.4%), specificity of 79.6% (95% CI: 70.3–88.9%) and 93.7% (95% CI: 90.7–96.8%), respectively, with an overall validation accuracy of 87%. The proposed model helps in identifying the DME-associated biomarkers, using 2D fundus images making it a promising tool for detecting and assessing DME-related features.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"35203-35218"},"PeriodicalIF":3.4000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10897982","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10897982/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract

Diabetes can impact the retina and cause a decline in vision for patients as a result of Diabetic Retinopathy (DR). Diabetic Macular Edema (DME) is a complication that results from the chronic damage to the tiny blood vessels of the retina that arises in the non-proliferative stage of DR (NPDR) but can also be present in proliferative DR (PDR) and potentially leading to vision loss. The duration of diabetes in patients affects both the prevalence and incidence of macular edema, as well as the progression of retinopathy. Therefore, regular screening of diabetes patients for the early detection of retinal abnormalities is essential to prevent the development and progression of DR and DME. The proposed model predicts DME-associated biomarkers, typically identified in Optical Coherence Tomography (OCT), using 2D fundus images. These biomarkers include center-involved diabetic macular edema (ci-DME), neurosensory detachment (NSD), Intraretinal fluid (IRF), disorganization of the retinal inner layers (DRIL), hyperreflective foci (HRF), and disruptions in the inner segment/outer segment (IS/OS) junction, utilizing 2D fundus images. The model integrates the feature extraction capability of ResNet50 with the spatial structural domain knowledge provided by the Swin attention augmentation layer. 2D fundus image datasets were collected to train and evaluate the model. In two distinct datasets, the model achieved a validation accuracy of 85.7% (95% CI: 81.6–90.6%) and 89.5% (95% CI: 85.6–93.4%), Cohen’s Kappa of 0.68 (95% CI: 0.61–0.77) and 0.75 (95% CI: 0.67–0.82), sensitivity of 88.6% (95% CI: 85.6–92.1%) and 79.6% (95% CI: 70.6–85.4%), specificity of 79.6% (95% CI: 70.3–88.9%) and 93.7% (95% CI: 90.7–96.8%), respectively, with an overall validation accuracy of 87%. The proposed model helps in identifying the DME-associated biomarkers, using 2D fundus images making it a promising tool for detecting and assessing DME-related features.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

9.80

自引率

7.70%

发文量

6673

审稿时长

6 weeks

期刊介绍： IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest. IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on: Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals. Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering. Development of new or improved fabrication or manufacturing techniques. Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.