Past year
All results
- All results
- Verbatim
Feb 29, 2024 · In this study, we developed an automated assessment module for color fundus photography image quality assessment using deep learning.
Apr 3, 2024 · This study aims to develop an automatic method for Retinal Image Quality Assessment (RIQA) that incorporates visual explanations, aiming to comprehensively ...
Sep 15, 2023 · We present a novel fundus image quality scale and deep learning (DL) model that can estimate fundus image quality relative to this new scale.
May 6, 2024 · The CFDL platforms were used to create deep learning models, with no preprocessing of the images, by a single ophthalmologist without coding expertise. The ...
Apr 3, 2024 · We propose an end-to-end deep learning framework for automatic DR grading (5 severity degrees) based on separating the attention of the dark structures from ...
Jun 24, 2024 · The proposed model of the deep neural network is designed for accurate detection and measurement of diabetic retinopathy using fundus images. A novel proposed ...
Jan 4, 2024 · We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images.
Jan 15, 2024 · This research develops a graphical user interface that integrates imaging algorithms to assess whether the patient's fundus image is affected by diabetic ...
Sep 14, 2023 · A deep learning model that can transform color fundus (CF) photography into corresponding venous and late-phase fundus fluorescein angiography (FFA) images.
Jan 15, 2024 · A deep learning (DL) model to assess fundus photograph quality, and quantitatively measure its impact on automated POAG detection in independent study ...