4 papers
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…
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…
Robust and efficient computation of retinal fractal dimension through deep approximation
Justin Engelmann, Ana Villaplana-Velasco, Amos Storkey +1
A retinal trait, or phenotype, summarises a specific aspect of a retinal image in a single number. This can then be used for further analyses, e.g. with statistical methods. Howeve…
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…