most citedImproved Automatic Diabetic Retinopathy Severity Classification Using Deep Multimodal Fusion of UWF-CFP and OCTA Images

21 citations · 49 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20241 cited

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…

cs.LG2024

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…

cs.CV2024

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…

eess.IV202418 cited

DISCOVER: 2-D Multiview Summarization of Optical Coherence Tomography Angiography for Automatic Diabetic Retinopathy Diagnosis

Mostafa El Habib Daho, Yihao Li, Rachid Zeghlache +12

Diabetic Retinopathy (DR), an ocular complication of diabetes, is a leading cause of blindness worldwide. Traditionally, DR is monitored using Color Fundus Photography (CFP), a wid…

cs.CV20235 cited

Longitudinal Self-supervised Learning Using Neural Ordinary Differential Equation

Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho +8

Longitudinal analysis in medical imaging is crucial to investigate the progressive changes in anatomical structures or disease progression over time. In recent years, a novel class…

eess.IV20234 cited

LMT: Longitudinal Mixing Training, a Framework to Predict Disease Progression from a Single Image

Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho +8

Longitudinal imaging is able to capture both static anatomical structures and dynamic changes in disease progression toward earlier and better patient-specific pathology management…