3 papers
eess.IV2023
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…
q-bio.QM2023
Evaluation of an automated choroid segmentation algorithm in a longitudinal kidney donor and recipient cohort
Jamie Burke, Dan Pugh, Tariq Farrah +7
Purpose: To evaluate the performance of an automated choroid segmentation algorithm in optical coherence tomography (OCT) data using a longitudinal kidney donor and recipient cohor…
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…