The Assessment of Retinal Image Quality Using a Non-Mydriatic Fundus Camera in a Teleophthalmologic Platform.
Tsung-Yueh ChanJen-Hung WangNancy ChenCheng-Jen ChiuPublished in: Diagnostics (Basel, Switzerland) (2024)
This study assesses the quality of retinal images captured using a non-mydriatic fundus camera within a teleophthalmologic platform in Taiwan. The objective was to evaluate the effectiveness of non-mydriatic fundus cameras for remote retinal screening and identify factors impacting image quality. From June 2020 to August 2022, 629 patients from five rural infirmaries underwent ophthalmic examinations, with fundus images captured without pupil dilation. These images were reviewed by senior ophthalmologists and graded based on quality. The results indicated that approximately 70% of images were of satisfactory diagnostic quality. Risk factors for poor image quality included older age, the presence of cataracts, pseudophakia, and diabetes mellitus. This study demonstrates the feasibility of using non-mydriatic fundus cameras for teleophthalmology, highlighting the importance of identifying and addressing factors that affect image quality to enhance diagnostic accuracy in remote settings.
Keyphrases
- image quality
- diabetic retinopathy
- optical coherence tomography
- convolutional neural network
- computed tomography
- deep learning
- dual energy
- end stage renal disease
- chronic kidney disease
- ejection fraction
- systematic review
- optic nerve
- quality improvement
- physical activity
- metabolic syndrome
- high throughput
- magnetic resonance
- type diabetes
- machine learning
- south africa
- magnetic resonance imaging
- peritoneal dialysis
- middle aged
- patient reported outcomes
- insulin resistance
- single cell
- contrast enhanced
- glycemic control