Eugenia Moris

Contact

emoris@pladema.exa.unicen.edu.ar
Pladema (new wing)
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Bio

Eugenia Moris (Euge) is a software engineer and a PhD student in Computational and Industrial Mathematics, specializing in the implementation of artificial intelligence in medical imaging. Her expertise ranges from the classification of structures in IVUS (Intravascular Ultrasound) to the classification of sleep stages in EEG (Electroencephalography). Currently, she is working on the segmentation of the optic disc and cup in fundus images for the early detection of ophthalmologic diseases.

Recent publications

Semi-supervised learning with Noisy Students improves domain generalization in optic disc and cup segmentation in uncropped fundus images
Eugenia Moris, Ignacio Larrabide, José Ignacio Orlando
Proceedings of Machine Learning Research

Assessing coarse-to-fine deep learning models for optic disc and cup segmentation in fundus images
Eugenia Moris, Nicolás Dazeo, María Paula Albina de Rueda, Francisco Filizzola, Nicolás Iannuzzo, Danila Nejamkin, Kevin Wignall, Mercedes Leguía, Ignacio Larrabide, José Ignacio Orlando
18th International Symposium on Medical Information Processing and Analysis

Evaluating sleep-stage classification: how age and early-late sleep affects classification performance
Eugenia Moris, Ignacio Larrabide
Medical & Biological Engineering & Computing

Award

Editor’s Choice
Evaluating sleep-stage classification: how age and early-late sleep affects classification performance
Medical & Biological Engineering & Computing