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20202024
most citedSLOctolyzer: Fully automatic analysis toolkit for segmentation and feature extracting in scanning laser ophthalmoscopy images

11 citations · 17 across the 11 of their papers we have counts for

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6 papers · 1 filter

eess.IV2024★ 3 cited

OCTolyzer: Fully automatic toolkit for segmentation and feature extracting in optical coherence tomography and scanning laser ophthalmoscopy data

Jamie Burke, Justin Engelmann, Samuel Gibbon +9

Optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO) of the eye has become essential to ophthalmology and the emerging field of oculomics, thus requiring a ne…

eess.IV2024★ 11 cited

SLOctolyzer: Fully automatic analysis toolkit for segmentation and feature extracting in scanning laser ophthalmoscopy images

Jamie Burke, Samuel Gibbon, Justin Engelmann +6

Purpose: The purpose of this study was to introduce SLOctolyzer: an open-source analysis toolkit for en face retinal vessels in infrared reflectance scanning laser ophthalmoscopy (…

eess.IV2024

Domain-specific augmentations with resolution agnostic self-attention mechanism improves choroid segmentation in optical coherence tomography images

Jamie Burke, Justin Engelmann, Charlene Hamid +9

The choroid is a key vascular layer of the eye, supplying oxygen to the retinal photoreceptors. Non-invasive enhanced depth imaging optical coherence tomography (EDI-OCT) has recen…

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…

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…