AIMC Topic: Visual Acuity

Clear Filters Showing 71 to 80 of 187 articles

Performance of retinal fluid monitoring in OCT imaging by automated deep learning versus human expert grading in neovascular AMD.

Eye (London, England)
PURPOSE: To evaluate the reliability of automated fluid detection in identifying retinal fluid activity in OCT scans of patients treated with anti-VEGF therapy for neovascular age-related macular degeneration by correlating human expert and automated...

An AI model to estimate visual acuity based solely on cross-sectional OCT imaging of various diseases.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop an artificial intelligence (AI) model for estimating best-corrected visual acuity (BCVA) using horizontal and vertical optical coherence tomography (OCT) scans of various retinal diseases and examine factors associated with its ac...

Efficacy and accuracy of artificial intelligence to overlay multimodal images from different optical instruments in patients with retinitis pigmentosa.

Clinical & experimental ophthalmology
BACKGROUND: Retinitis pigmentosa (RP) represents a group of progressive, genetically heterogenous blinding diseases. Recently, relationships between measures of retinal function and structure are needed to help identify outcome measures or biomarkers...

Cuttlefish eye-inspired artificial vision for high-quality imaging under uneven illumination conditions.

Science robotics
With the rise of mobile robotics, including self-driving automobiles and drones, developing artificial vision for high-contrast and high-acuity imaging in vertically uneven illumination conditions has become an important goal. In such situations, bal...

KFWC: A Knowledge-Driven Deep Learning Model for Fine-grained Classification of Wet-AMD.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automated diagnosis using deep neural networks can help ophthalmologists detect the blinding eye disease wet Age-related Macular Degeneration (AMD). Wet-AMD has two similar subtypes, Neovascular AMD and Polypoidal Choroidal...

Artificial intelligence using deep learning to predict the anatomical outcome of rhegmatogenous retinal detachment surgery: a pilot study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop and evaluate an automated deep learning model to predict the anatomical outcome of rhegmatogenous retinal detachment (RRD) surgery.

Estimation of best corrected visual acuity based on deep neural network.

Scientific reports
In this study, we investigated a convolutional neural network (CNN)-based framework for the estimation of the best-corrected visual acuity (BCVA) from fundus images. First, we collected 53,318 fundus photographs from the Gyeongsang National Universit...

Randomised controlled trial on robot-assisted versus manual surgery for pucker peeling.

Clinical & experimental ophthalmology
BACKGROUND: The aim was to explore the feasibility and safety of performing common surgical steps in epiretinal membrane (ERM) peeling using the Preceyes Surgical System (PSS).

Prediction of the response to photodynamic therapy in patients with chronic central serous chorioretinopathy based on optical coherence tomography using deep learning.

Photodiagnosis and photodynamic therapy
PURPOSE: To assess the prediction of the response to photodynamic therapy (PDT) in chronic central serous chorioretinopathy (CSCR) based on spectral-domain optical coherence tomography (SD-OCT) images using deep learning (DL).