Publications by authors named "L de Sisternes"
Purpose: Although structural OCT is traditionally used to differentiate the vascular plexus layers in OCT angiography (OCTA), the vascular plexuses do not always obey the retinal laminations. We sought to segment the superficial, deep, and avascular plexuses from OCTA images using deep learning without structural OCT image input or segmentation boundaries.
Design: Cross-sectional study.
Article Synopsis
- - The study aims to quantify uncertainty in deep learning segmentation of geographic atrophy (GA) using retrospective OCT image analysis from the SWAGGER cohort.
- - Two Bayesian deep learning techniques, Monte Carlo dropout and ensemble methods, were developed and compared against a traditional model, focusing on segmenting GA lesions and evaluating their performance with Dice scores and Shannon Entropy.
- - Results showed that the Bayesian models had higher Dice scores (0.90 and 0.88) and greater pixel-level uncertainty compared to the traditional model (0.82), suggesting that these techniques may enhance model reliability and assist clinicians in their decision-making for GA.
Purpose: An algorithm developed to obtain drusen area and volume measurements using swept-source OCT angiography (SS-OCTA) scans was tested on spectral-domain OCT angiography (SD-OCTA) scans.
Design: Retrospective study.
Participants: Forty pairs of scans from 27 eyes with intermediate age-related macular degeneration and drusen.
Background: This study aimed to develop a deep learning (DL) algorithm that enhances the quality of a single-frame enface OCTA scan to make it comparable to 4-frame averaged scan without the need for the repeated acquisitions required for averaging.
Methods: Each of the healthy eyes and eyes from diabetic subjects that were prospectively enrolled in this cross-sectional study underwent four repeated 6 × 6 mm macular scans (PLEX Elite 9000 SS-OCT), and the repeated scans of each eye were co-registered to produce 4-frame averages. This prospective dataset of original (single-frame) enface scans and their corresponding averaged scans was divided into a training dataset and a validation dataset.
Purpose: Choroidal changes before and after anti-VEGF therapy were investigated in eyes with exudative AMD to determine if there was a difference between eyes with macular neovascularization (MNV) that arises from the choroid (type 1 or 2) versus the retinal circulation (type 3).
Methods: Patients with treatment-naïve AMD were imaged with swept-source optical coherence tomography angiography using a 12 × 12-mm scan pattern. The mean choroidal thickness and choroidal vascularity index (CVI) were measured within 5-mm and 11-mm fovea-centered circles before, at the onset of, and after anti-VEGF therapy.