A Novel Hybrid Retinal Blood Vessel Segmentation Algorithm for Enlarging the Measuring Range of Dual-Wavelength Retinal Oximetry DOI Creative Commons
Yongli Xian, Guangxin Zhao, Congzheng Wang

и другие.

Photonics, Год журнала: 2023, Номер 10(7), С. 722 - 722

Опубликована: Июнь 24, 2023

The non-invasive measurement of hemoglobin oxygen saturation (SO2) in retinal vessels is based on spectrophotometry and the absorption spectral characteristics tissue. dual-wavelength images are simultaneously captured via oximetry. SO2 calculated by processing a series calculating optic density ratio two images. However, existing research focused thick high-clarity region thin low-clarity could provide significant information for detection diagnosis neovascular diseases. To this end, we proposed novel hybrid vessel segmentation algorithm. Firstly, median filter was employed image denoising. Secondly, high- carried out clarity histogram. areas were segmented after implementing Gaussian filter, matched morphological segmentation. Additionally, using guided filtering, dynamic threshold Finally, results obtained through merger operations. experimental analysis show that method can effectively segment extend measuring range

Язык: Английский

The Role of Artificial Intelligence in Epiretinal Membrane Care: A Scoping Review DOI Creative Commons
David Mikhail, Daniel Milad, Fares Antaki

и другие.

Ophthalmology Science, Год журнала: 2024, Номер unknown, С. 100689 - 100689

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

3

Application of Multimodal Imaging in the Diagnosis and Treatment of Epiretinal Membrane DOI

鸿民 李

Advances in Clinical Medicine, Год журнала: 2025, Номер 15(01), С. 676 - 683

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Performance of artificial intelligence-based models for epiretinal membrane diagnosis: A systematic review and meta-analysis DOI Creative Commons
David Mikhail,

Angel Gao,

A Farah

и другие.

American Journal of Ophthalmology, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Epiretinal membrane (ERM) can impair central vision by forming a pre-retinal fibrous layer on the inner retina. Artificial intelligence (AI)-based tools may streamline ERM diagnosis, but their overall performance and factors affecting accuracy require evaluation. With an aging population, prevalence is expected to rise, placing increased demands clinical resources. Early detection via AI models could expedite reduce subjective errors, guide timely surgical intervention. This systematic review meta-analysis evaluates pooled diagnostic of for detecting identifies study- model-level influencing performance. Systematic Review Meta-Analysis METHODS: Comprehensive searches were conducted in Medline, Embase, Cochrane Library, Web Science, preprint databases from inception June 2024. Included studies evaluated diagnosis. Study quality risk bias assessed using Quality Assessment Diagnostic Accuracy Studies 2 (QUADAS-2) tool. A random-effects model was applied pool accuracy, sensitivity, specificity, odds ratio. Subgroup analyses explored The study protocol registered with International Prospective Register Reviews (PROSPERO - CRD42024563571). Of 379 articles screened, 26 met inclusion criteria, 19 contributed meta-analysis. settings predominantly hospital-based (76.9%), some academic computer biomedical science departments (15.4%) community centers (7.7%). assessments suggested low or unclear applicability concerns 95% studies. sensitivity 90.1% (95% CI: 85.8-93.2), specificity 95.7% 88.8-95.2). analysis showed higher (97.1%, 96.0-97.9) color fundus photographs than optical coherence tomography scans, which had 92.6% External validation performed 26.9% All included used expert human grading as reference standard, 25 (96.2%) based same imaging modality input. proportion cases development datasets varied across studies, particularly between single-disease multiclass models. demonstrate high ERM. However, limited external variability methodologies limits direct comparison real-world applicability. Future work should standardize reporting practices, improve data interoperability, develop prediction track disease progression determine optimal timing.

Язык: Английский

Процитировано

0

Haemorrhage diagnosis in colour fundus images using a fast-convolutional neural network based on a modified U-Net DOI

R. Sathiyaseelan,

R. Krishnamoorthy,

Ramesh Ramamoorthy

и другие.

Network Computation in Neural Systems, Год журнала: 2024, Номер unknown, С. 1 - 22

Опубликована: Фев. 12, 2024

Retinal haemorrhage stands as an early indicator of diabetic retinopathy, necessitating accurate detection for timely diagnosis. Addressing this need, study proposes enhanced machine-based diagnostic test retinopathy through updated UNet framework, adept at scrutinizing fundus images signs retinal haemorrhages. The customized underwent GPU training using the IDRiD database, validated against publicly available DIARETDB1 and datasets. Emphasizing complexity segmentation, employed preprocessing techniques, augmenting image quality data integrity. Subsequently, trained neural network showcased a remarkable performance boost, accurately identifying regions with 80% sensitivity, 99.6% specificity, 98.6% accuracy. experimental findings solidify network's reliability, showcasing potential to alleviate ophthalmologists' workload significantly. Notably, achieving Intersection over Union (IoU) 76.61% Dice coefficient 86.51% underscores system's competence. study's outcomes signify substantial enhancements in diagnosing critical conditions, promising profound improvements accuracy efficiency, thereby marking significant advancement automated retinopathy.

Язык: Английский

Процитировано

2

A Novel Hybrid Retinal Blood Vessel Segmentation Algorithm for Enlarging the Measuring Range of Dual-Wavelength Retinal Oximetry DOI Creative Commons
Yongli Xian, Guangxin Zhao, Congzheng Wang

и другие.

Photonics, Год журнала: 2023, Номер 10(7), С. 722 - 722

Опубликована: Июнь 24, 2023

The non-invasive measurement of hemoglobin oxygen saturation (SO2) in retinal vessels is based on spectrophotometry and the absorption spectral characteristics tissue. dual-wavelength images are simultaneously captured via oximetry. SO2 calculated by processing a series calculating optic density ratio two images. However, existing research focused thick high-clarity region thin low-clarity could provide significant information for detection diagnosis neovascular diseases. To this end, we proposed novel hybrid vessel segmentation algorithm. Firstly, median filter was employed image denoising. Secondly, high- carried out clarity histogram. areas were segmented after implementing Gaussian filter, matched morphological segmentation. Additionally, using guided filtering, dynamic threshold Finally, results obtained through merger operations. experimental analysis show that method can effectively segment extend measuring range

Язык: Английский

Процитировано

4