11 citations · 16 across the 7 of their papers we have counts for
6 papers · 1 filter
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…
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 (…
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…
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…
A method for quantifying sectoral optic disc pallor in fundus photographs and its association with peripapillary RNFL thickness
Samuel Gibbon, Graciela Muniz-Terrera, Fabian SL Yii +8
Purpose: To develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fibre layer (pRNFL) thick…
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…