Search Results for author: Megan Reid-Schachter

Found 2 papers, 2 papers with code

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

1 code implementation • 5 Dec 2023 • Justin Engelmann, Jamie Burke, Charlene Hamid, Megan Reid-Schachter, Dan Pugh, Neeraj Dhaun, Diana Moukaddem, Lyle Gray, Niall Strang, Paul McGraw, Amos Storkey, Paul J. Steptoe, Stuart King, Tom MacGillivray, Miguel O. Bernabeu, Ian J. C. MacCormick

We analysed segmentation agreement (AUC, Dice) and choroid metrics agreement (Pearson, Spearman, mean absolute error (MAE)) in internal and external test sets.

Segmentation

Paper
Code

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

1 code implementation • 3 Jul 2023 • Jamie Burke, Justin Engelmann, Charlene Hamid, Megan Reid-Schachter, Tom Pearson, Dan Pugh, Neeraj Dhaun, Stuart King, Tom MacGillivray, Miguel O. Bernabeu, Amos Storkey, Ian J. C. MacCormick

Results: DeepGPET achieves excellent agreement with GPET on data from 3 clinical studies (AUC=0. 9994, Dice=0. 9664; Pearson correlation of 0. 8908 for choroidal thickness and 0. 9082 for choroidal area), while reducing the mean processing time per image on a standard laptop CPU from 34. 49s ($\pm$15. 09) using GPET to 1. 25s ($\pm$0. 10) using DeepGPET.

Segmentation

Paper
Code

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