most citedCoarse-to-fine Surgical Instrument Detection for Cataract Surgery Monitoring

4 citations · 5 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

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.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…

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…

cs.CV20161 cited

Real-time analysis of cataract surgery videos using statistical models

Katia Charrière, Gwenolé Quellec, Mathieu Lamard +4

The automatic analysis of the surgical process, from videos recorded during surgeries, could be very useful to surgeons, both for training and for acquiring new techniques. The tra…

cs.CV20164 cited

Coarse-to-fine Surgical Instrument Detection for Cataract Surgery Monitoring

Hassan Al Hajj, Gwenolé Quellec, Mathieu Lamard +2

The amount of surgical data, recorded during video-monitored surgeries, has extremely increased. This paper aims at improving existing solutions for the automated analysis of catar…