activity
20122024
most citedComputer simulations reveal complex distribution of haemodynamic forces in a mouse retina model of angiogenesis

117 citations · 360 across the 15 of their papers we have counts for

collaborators

16 papers

q-bio.QM2024

Applicability of oculomics for individual risk prediction: Repeatability and robustness of retinal Fractal Dimension using DART and AutoMorph

Justin Engelmann, Diana Moukaddem, Lucas Gago +2

Purpose: To investigate whether Fractal Dimension (FD)-based oculomics could be used for individual risk prediction by evaluating repeatability and robustness. Methods: We used two…

eess.IV2023★ 1 cited

Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography

Justin Engelmann, Jamie Burke, Charlene Hamid +13

Purpose: To develop Choroidalyzer, an open-source, end-to-end pipeline for segmenting the choroid region, vessels, and fovea, and deriving choroidal thickness, area, and vascular i…

cs.CV2023

QuickQual: Lightweight, convenient retinal image quality scoring with off-the-shelf pretrained models

Justin Engelmann, Amos Storkey, Miguel O. Bernabeu

Image quality remains a key problem for both traditional and deep learning (DL)-based approaches to retinal image analysis, but identifying poor quality images can be time consumin…

eess.IV2023★ 1 cited

An open-source deep learning algorithm for efficient and fully-automatic analysis of the choroid in optical coherence tomography

Jamie Burke, Justin Engelmann, Charlene Hamid +9

Purpose: To develop an open-source, fully-automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data. Methods: We used…

eess.IV2022

Detection of multiple retinal diseases in ultra-widefield fundus images using deep learning: data-driven identification of relevant regions

Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick +3

Ultra-widefield (UWF) imaging is a promising modality that captures a larger retinal field of view compared to traditional fundus photography. Previous studies showed that deep lea…

cs.CV2021

Global explainability in aligned image modalities

Justin Engelmann, Amos Storkey, Miguel O. Bernabeu

Deep learning (DL) models are very effective on many computer vision problems and increasingly used in critical applications. They are also inherently black box. A number of method…