1.1k citations
- InsermFR28 papers
- Centre National de la Recherche ScientifiqueFR27 papers
- Sorbonne UniversitéFR19 papers
- Centre de Recherche en Acquisition et Traitement de l'Image pour la SantéFR10 papers
- Lyon 1 UniversitéFR7 papers
- Université Paris-SaclayFR6 papers
- Hospices Civils de LyonFR5 papers
- Assistance Publique – Hôpitaux de ParisFR4 papers
- Institut du CerveauFR4 papers
- Institut National des Sciences Appliquées de LyonFR4 papers
- University of PennsylvaniaUS4 papers
- CEA Paris-SaclayFR3 papers
66 papers
Imaging of ultrasound specularity at cortical bone interfaces to detect unbalanced remodeling: A preliminary study
Amadou S. Dia, Salomé Vignat, Guillaume Renaud +1
The region near the interface between cortical bone and the medullary cavity (the endosteal surface) is of particular interest for the early detection of osteoporosis. This region…
MedTutor: A Retrieval-Augmented LLM System for Case-Based Medical Education
Dongsuk Jang, Ziyao Shangguan, Kyle Tegtmeyer +4
The learning process for medical residents presents significant challenges, demanding both the ability to interpret complex case reports and the rapid acquisition of accurate medic…
A Geometric Multimodal Foundation Model Integrating Bp-MRI and Clinical Reports in Prostate Cancer Classification
Juan A. Olmos, Antoine Manzanera, Fabio Martínez
Prostate cancer (PCa) is one of the most common cancers in men worldwide. Bi-parametric MRI (bp-MRI) and clinical variables are crucial for PCa identification and improving treatme…
Estimation of Segmental Longitudinal Strain in Transesophageal Echocardiography by Deep Learning
Anders Austlid Taskén, Thierry Judge, Erik Andreas Rye Berg +8
Segmental longitudinal strain (SLS) of the left ventricle (LV) is an important prognostic indicator for evaluating regional LV dysfunction, in particular for diagnosing and managin…
OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection
Nicolas Pinon, Robin Trombetta, Carole Lartizien
Unsupervised anomaly detection (UAD) aims to detect anomalies without labeled data, a necessity in many machine learning applications where anomalous samples are rare or not availa…
dCMF: Learning interpretable evolving patterns from temporal multiway data
Christos Chatzis, Carla Schenker, Jérémy E. Cohen +1
Multiway datasets are commonly analyzed using unsupervised matrix and tensor factorization methods to reveal underlying patterns. Frequently, such datasets include timestamps and c…