no code implementations • 23 Apr 2024 • Yihao Li, Mostafa El Habib Daho, Pierre-Henri Conze, Rachid Zeghlache, Hugo Le Boité, Ramin Tadayoni, Béatrice Cochener, Mathieu Lamard, Gwenolé Quellec
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 understanding of the underlying pathology.
no code implementations • 10 Apr 2024 • Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Hugo Le Boité, Ramin Tadayoni, Pascal Massin, Béatrice Cochener, Alireza Rezaei, Ikram Brahim, Gwenolé Quellec, Mathieu Lamard
This work proposes a novel framework for analyzing disease progression using time-aware neural ordinary differential equations (NODE).
no code implementations • 24 Mar 2024 • Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Alireza Rezaei, Hugo Le Boité, Ramin Tadayoni, Pascal Massin, Béatrice Cochener, Ikram Brahim, Gwenolé Quellec, Mathieu Lamard
Our results demonstrated the relevancy of both time-aware position embedding and masking strategies based on disease progression knowledge.
no code implementations • 10 Jan 2024 • Mostafa El Habib Daho, Yihao Li, Rachid Zeghlache, Hugo Le Boité, Pierre Deman, Laurent Borderie, Hugang Ren, Niranchana Mannivanan, Capucine Lepicard, Béatrice Cochener, Aude Couturier, Ramin Tadayoni, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec
A straightforward solution to this task is a 3-D neural network classifier.
1 code implementation • 8 Jan 2024 • Yihao Li, Philippe Zhang, Yubo Tan, Jing Zhang, Zhihan Wang, Weili Jiang, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec, Mostafa El Habib Daho
As for Task 3 (prediction of spherical equivalent), we have designed a deep regression model based on the data distribution of the dataset and employed an integration strategy to enhance the model's prediction accuracy.
no code implementations • 16 Oct 2023 • Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Hugo Le Boité, Ramin Tadayoni, Pascal Massin, Béatrice Cochener, Ikram Brahim, Gwenolé Quellec, Mathieu Lamard
In recent years, a novel class of algorithms has emerged with the goal of learning disease progression in a self-supervised manner, using either pairs of consecutive images or time series of images.
no code implementations • 16 Oct 2023 • Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Hugo Le boite, Ramin Tadayoni, Pascal Massin, Béatrice Cochener, Ikram Brahim, Gwenolé Quellec, Mathieu Lamard
Our framework, Longitudinal Mixing Training (LMT), can be considered both as a regularizer and as a pretext task that encodes the disease progression in the latent space.
no code implementations • 3 Oct 2023 • Mostafa El Habib Daho, Yihao Li, Rachid Zeghlache, Yapo Cedric Atse, Hugo Le Boité, Sophie Bonnin, Deborah Cosette, Pierre Deman, Laurent Borderie, Capucine Lepicard, Ramin Tadayoni, Béatrice Cochener, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec
Diabetic Retinopathy (DR), a prevalent and severe complication of diabetes, affects millions of individuals globally, underscoring the need for accurate and timely diagnosis.
no code implementations • 5 Apr 2023 • Bo Qian, Hao Chen, Xiangning Wang, Haoxuan Che, Gitaek Kwon, Jaeyoung Kim, Sungjin Choi, Seoyoung Shin, Felix Krause, Markus Unterdechler, Junlin Hou, Rui Feng, Yihao Li, Mostafa El Habib Daho, Qiang Wu, Ping Zhang, Xiaokang Yang, Yiyu Cai, Weiping Jia, Huating Li, Bin Sheng
Computer-assisted automatic analysis of diabetic retinopathy (DR) is of great importance in reducing the risks of vision loss and even blindness.
1 code implementation • 21 Nov 2022 • Yihao Li, Rachid Zeghlache, Ikram Brahim, Hui Xu, Yubo Tan, Pierre-Henri Conze, Mathieu Lamard, Gwenolé Quellec, Mostafa El Habib Daho
Diabetic Retinopathy (DR) is a severe complication of diabetes that can cause blindness.
no code implementations • 2 Sep 2022 • Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Ramin Tadayoni, Pascal Massin, Béatrice Cochener, Gwenolé Quellec, Mathieu Lamard
Longitudinal imaging is able to capture both static anatomical structures and dynamic changes in disease progression towards earlier and better patient-specific pathology management.
no code implementations • 2 Sep 2022 • Yihao Li, Mostafa El Habib Daho, Pierre-Henri Conze, Hassan Al Hajj, Sophie Bonnin, Hugang Ren, Niranchana Manivannan, Stephanie Magazzeni, Ramin Tadayoni, Béatrice Cochener, Mathieu Lamard, Gwenolé Quellec
In recent years, multiple imaging techniques have been used in clinical practice for retinal analysis: 2D fundus photographs, 3D optical coherence tomography (OCT) and 3D OCT angiography, etc.