Semi-supervised learning with Noisy Students improves domain generalization in optic disc and cup segmentation in uncropped fundus images

The paper evaluates domain generalization strategies for optic disc and cup segmentation in fundus images, highlighting issues with existing methods when applied to uncropped images, and proposes a semi-supervised learning approach based on the Noisy Student framework to improve performance across diverse datasets.

Assessing Coarse-to-Fine Deep Learning Models for Optic Disc and Cup Segmentation in Fundus Images

We experimentally validate whether using coarse-to-fine models instead of one-stage models is appropriate or not for segmenting the optic disc and the optic cup in color fundus images. We observed that models trained with the right amount of data can perform much better than coarse-to-find approaches.

Cómo entrenar bien un baseline - Experiencias y recomendaciones desde la aplicación de deep learning en oftalmología

Cuando aplicamos inteligencia artificial en medicina, solemos seguir uno de dos enfoques: o bien utilizar modelos que ya existen para resolver un problema nuevo, o bien proponer un modelo nuevo para resolver problemas que ya existen. En todos los …

Inteligencia artificial en oftalmología - desarrollos argentinos, oportunidades y desafíos

Voy a presentar algunas de las líneas de trabajo actuales en inteligencia artificial aplicada a la oftalmología que llevo adelante, repasando además algunos desarrollos previos en los que participé durante mi estadía postdoctoral en Austria.

AGE Challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography

This is the summary publication of the AGE challenge on angle closure glaucoma detection from OCT scans of the anterior segment.

What's next in AI for glaucoma screening? The REFUGE challenge outcomes

I will present some of the conclusions of the REFUGE challenge on glaucoma assessment from fundus pictures, and my personal view on what's still needed to progress towards automated screening of glaucoma from fundus pictures.

Towards a better understanding of glaucoma through fundus photography

Computation and discovery of glaucoma biomarkers from color fundus photographs

REFUGE challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs

This is the summary publication of the REFUGE challenge on glaucoma detection in color fundus photographs.

Convocatoria para Estudiantes Avanzados de Ingeniería - EVC-CIN 2019

Estamos entrevistando candidatos para aplicar a las becas de estímulo a las vocaciones científicas EVC 2019 del CIN (Consejo Universitario Nacional).

U2-Net: A Bayesian U-Net Model with Epistemic Uncertainty Feedback for Photoreceptor Layer Segmentation in Pathological OCT Scans

Our ISBI paper was selected for oral presentation at the Eye Imaging Analysis session in ISBI 2019. Hope to see you there!