output
20062026
most citedDeep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography

773 citations

researchers with a paper here
collaborating institutions

89 papers

cs.AI2026

Gradient Step Plug-and-Play Model for Dental Cone-Beam CT Reconstruction

Idris Tatachak, Luis Kabongo, Nicolas Papadakis +2

The goal of this work is to reduce the effect of photon noise in dental cone-beam CT reconstruction. We consider an inverse problem formulation and develop a databased prior. To th…

cs.CV2026

A convergent Plug-and-Play Majorization-Minimization algorithm for Poisson inverse problems

Thibaut Modrzyk, Ane Etxebeste, Élie Bretin +1

In this paper, we present a novel variational plug-and-play algorithm for Poisson inverse problems. Our approach minimizes an explicit functional which is the sum of a Kullback-Lei…

cond-mat.mtrl-sci2025

Unveiling Solvent Effects on Femtosecond Laser-Irradiated Au/Fe3O4 Colloidal Nanoparticles: The Acetone Effect

Stéphane Mottin, Żaneta Świątkowska-Warkocka, Marta Wolny-Marszałek +1

The interplay between laser parameters and liquid environments dictates the outcome of femtosecond laser-induced nanoparticle modification. We present a study of gold and iron oxid…

cs.CV2025★ 4 cited

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…

cs.CV2025

Structured Spectral Graph Representation Learning for Multi-label Abnormality Analysis from 3D CT Scans

Theo Di Piazza, Carole Lazarus, Olivier Nempont +1

With the growing volume of CT examinations, there is an increasing demand for automated tools such as organ segmentation, abnormality detection, and report generation to support ra…

cs.LG2025★ 1 cited

Gated X-TFC: Soft Domain Decomposition for Forward and Inverse Problems in Sharp-Gradient PDEs

Vikas Dwivedi, Enrico Schiassi, Monica Sigovan +1

Physics-informed neural networks (PINNs) and related methods struggle to resolve sharp gradients in singularly perturbed boundary value problems without resorting to some form of d…