output
20202025
most citedTowards defining reference materials for extracellular vesicle size, concentration, refractive index and epitope abundance

150 citations

15 papers

cs.CV20251 cited

Federated Fine-tuning of SAM-Med3D for MRI-based Dementia Classification

Kaouther Mouheb, Marawan Elbatel, Janne Papma +8

While foundation models (FMs) offer strong potential for AI-based dementia diagnosis, their integration into federated learning (FL) systems remains underexplored. In this benchmar…

physics.med-ph2024

Acquisition-Independent Deep Learning for Quantitative MRI Parameter Estimation using Neural Controlled Differential Equations

Daan Kuppens, Sebastiano Barbieri, Daisy van den Berg +4

Deep learning has proven to be a suitable alternative to least-squares (LSQ) fitting for parameter estimation in various quantitative MRI (QMRI) models. However, current deep learn…

math.OC2024

Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application to Parkinson's Disease trajectory modelling

Alessandro Viani, Boris A Gutman, Emile d'Angremont +1

Modelling the progression of Degenerative Diseases (DD) is essential for detection, prevention, and treatment, yet it remains challenging due to the heterogeneity in disease trajec…

q-bio.QM2024

MRI-based and metabolomics-based age scores act synergetically for mortality prediction shown by multi-cohort federated learning

Pedro Mateus, Swier Garst, Jing Yu +19

Biological age scores are an emerging tool to characterize aging by estimating chronological age based on physiological biomarkers. Various scores have shown associations with agin…

eess.IV20236 cited

TabAttention: Learning Attention Conditionally on Tabular Data

Michal K. Grzeszczyk, Szymon Płotka, Beata Rebizant +6

Medical data analysis often combines both imaging and tabular data processing using machine learning algorithms. While previous studies have investigated the impact of attention me…

eess.IV202331 cited

Robust deformable image registration using cycle-consistent implicit representations

Louis D. van Harten, Jaap Stoker, Ivana Išgum

Recent works in medical image registration have proposed the use of Implicit Neural Representations, demonstrating performance that rivals state-of-the-art learning-based methods.…