21 citations · 61 across the 15 of their papers we have counts for
16 papers
CornOrb: A Multimodal Dataset of Orbscan Corneal Topography and Clinical Annotations for Keratoconus Detection
Mohammed El Amine Lazouni, Leila Ryma Lazouni, Zineb Aziza Elaouaber +8
In this paper, we present CornOrb, a publicly accessible multimodal dataset of Orbscan corneal topography images and clinical annotations collected from patients in Algeria. The da…
Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge
Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47
The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…
Deep Learning-Based Detection of Referable Diabetic Retinopathy and Macular Edema Using Ultra-Widefield Fundus Imaging
Philippe Zhang, Pierre-Henri Conze, Mathieu Lamard +2
Diabetic retinopathy and diabetic macular edema are significant complications of diabetes that can lead to vision loss. Early detection through ultra-widefield fundus imaging enhan…
A review of deep learning-based information fusion techniques for multimodal medical image classification
Yihao Li, Mostafa El Habib Daho, Pierre-Henri Conze +6
Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it combines information from various imaging modalities to provide a more comprehensive under…
LaTiM: Longitudinal representation learning in continuous-time models to predict disease progression
Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho +9
This work proposes a novel framework for analyzing disease progression using time-aware neural ordinary differential equations (NODE). We introduce a "time-aware head" in a framewo…
L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction
Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho +9
Pre-training strategies based on self-supervised learning (SSL) have proven to be effective pretext tasks for many downstream tasks in computer vision. Due to the significant dispa…