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7 papers · 2 filters
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…
Improved Automatic Diabetic Retinopathy Severity Classification Using Deep Multimodal Fusion of UWF-CFP and OCTA Images
Mostafa El Habib Daho, Yihao Li, Rachid Zeghlache +12
Diabetic Retinopathy (DR), a prevalent and severe complication of diabetes, affects millions of individuals globally, underscoring the need for accurate and timely diagnosis. Recen…
Using deep learning for an automatic detection and classification of the vascular bifurcations along the Circle of Willis
Rafic Nader, Romain Bourcier, Florent Autrusseau
Most of the intracranial aneurysms (ICA) occur on a specific portion of the cerebral vascular tree named the Circle of Willis (CoW). More particularly, they mainly arise onto fifte…
Cross-dimensional transfer learning in medical image segmentation with deep learning
Hicham Messaoudi, Ahror Belaid, Douraied Ben Salem +1
Over the last decade, convolutional neural networks have emerged and advanced the state-of-the-art in various image analysis and computer vision applications. The performance of 2D…
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities
Nicolas Pinon, Robin Trombetta, Carole Lartizien
Anomaly detection remains a challenging task in neuroimaging when little to no supervision is available and when lesions can be very small or with subtle contrast. Patch-based repr…
Learning with minimal effort: leveraging in silico labeling for cell and nucleus segmentation
Thomas Bonte, Maxence Philbert, Emeline Coleno +3
Deep learning provides us with powerful methods to perform nucleus or cell segmentation with unprecedented quality. However, these methods usually require large training sets of ma…