most citedCarotid Artery Plaque Analysis in 3D Based on Distance Encoding in Mesh Representations

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2026

Comparative Evaluation of Carotid Artery Hemodynamics: Patient-Specific CFD Simulations vs. 4D flow MRI

Ali Mokhtari, Merel Meulendijks, Ariel Bergmann +4

Wall shear stress (WSS) is implicated in carotid atherosclerosis, and 4D flow MRI offers a non-invasive route to its estimation, but the agreement of MRI-derived plaque-surface WSS…

cs.CV2026

Segmentation of the aorta in 4D flow MRI using 4D convolutional kernels and learning from sparse annotations

Hinrich Rahlfs, Julio Garcia, Chiara Manini +13

Automated aortic segmentation in 4D flow MRI is essential for reproducible hemodynamic assessment but is limited by scarce dense annotations and high computational demands. We deve…

eess.IV2026

CaroTo: A Tool for Fast Comprehensive Analysis of Carotid Artery Stenosis in 4D PC- and 3D BB-MRI Data

Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +4

Atherosclerosis of the carotid artery increases stroke risk. Atherosclerosis assessment with MRI requires multimodal and multidimensional segmentation of the carotid artery, reprod…

cs.CV2025★ 2 cited

Carotid Artery Plaque Analysis in 3D Based on Distance Encoding in Mesh Representations

Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +3

Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D through extraction and visualization of quantitative plaque parameters. These parameters hav…

cs.CV2025★ 1 cited

Learning Wall Segmentation in 3D Vessel Trees using Sparse Annotations

Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +3

We propose a novel approach that uses sparse annotations from clinical studies to train a 3D segmentation of the carotid artery wall. We use a centerline annotation to sample perpe…