Search Results for author:
Found 4 papers, 3 papers with code
Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography
We analysed segmentation agreement (AUC, Dice) and choroid metrics agreement (Pearson, Spearman, mean absolute error (MAE)) in internal and external test sets.
A method for quantifying sectoral optic disc pallor in fundus photographs and its association with peripapillary RNFL thickness
Conclusions: We developed software that automatically locates and quantifies disc pallor in fundus photographs and found associations between pallor measurements and pRNFL thickness.
An open-source deep learning algorithm for efficient and fully-automatic analysis of the choroid in optical coherence tomography
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.
Evaluation of an automated choroid segmentation algorithm in a longitudinal kidney donor and recipient cohort
Significant associations were mostly stronger with automated CT (eGFR P<0. 001, creatinine P=0. 004, urea P=0. 04) compared to manual CT (eGFR P=0. 002, creatinine P=0. 01, urea P=0. 03).
