Aug 5, 2019 · Accurate inference of VFT measurements from OCT could reduce examination time and cost. We propose a novel 3D Convolutional Neural Network (CNN) ...

Conclusions : A deep learning approach trained on ONH scans can infer VFI and MD directly from raw OCT volumes. This technique significantly outperformed all ...

To develop a deep learning model to estimate the visual field (VF) from spectral-domain optical coherence tomography (SD-OCT) and swept-source OCT (SS-OCT)

Accurate inference of VFT measurements from OCT could reduce examination time and cost. We propose a novel 3D Convolutional Neural Network (CNN) for this task ...

Jun 4, 2021 · Two deep learning models based on Inception-ResNet-v2 were trained to estimate 24-2 VF from SS-OCT and SD-OCT images. The estimation performance ...

Oct 6, 2022 · This study built an OCT-based deep learning model that inferred VA status based on OCT and was correlated with the concurrent BCVA measured by ...

Dec 5, 2022 · The purpose of this study was to develop a deep learning model to predict 10-2 VF from wide-field SS-OCT images and evaluate its performance.

Aug 5, 2019 · Accurate inference of VFT measurements from OCT could reduce examination time and cost. We propose a novel 3D Convolutional Neural Network (CNN) ...

Deep learning models enable the estimation of visual field loss from optical coherence tomography angiography images with high accuracy. •. Applying deep ...

To develop and validate a deep learning (DL) system for predicting each point on visual fields (VFs) from disc and OCT imaging and derive a structure–function ...