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From the 1 of 54 linked papers with an AI index.

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20242026
most citedThe TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

12 citations · 14 across the 17 of their papers we have counts for

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Showing 2025Show all

17 papers · 1 filter

eess.IV2025

Disentangling Progress in Medical Image Registration: Beyond Trend-Driven Architectures towards Domain-Specific Strategies

Bailiang Jian, Jiazhen Pan, Rohit Jena +5

Medical image registration drives quantitative analysis across organs, modalities, and patient populations. Recent deep learning methods often combine low-level "trend-driven" comp…

cs.CV2025

MultiMAE for Brain MRIs: Robustness to Missing Inputs Using Multi-Modal Masked Autoencoder

Ayhan Can Erdur, Christian Beischl, Daniel Scholz +4

Missing input sequences are common in medical imaging data, posing a challenge for deep learning models reliant on complete input data. In this work, inspired by MultiMAE [2], we d…

cs.CV2025

Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models

Zeineb Haouari, Jonas Weidner, Yeray Martin-Ruisanchez +5

Glioblastoma, a highly aggressive brain tumor, poses major challenges due to its poor prognosis and high morbidity rates. Partial differential equation-based models offer promising…

eess.IV2025

MM-DINOv2: Adapting Foundation Models for Multi-Modal Medical Image Analysis

Daniel Scholz, Ayhan Can Erdur, Viktoria Ehm +4

Vision foundation models like DINOv2 demonstrate remarkable potential in medical imaging despite their origin in natural image domains. However, their design inherently works best…

eess.IV2025

Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method

Daniel Scholz, Ayhan Can Erdur, Robbie Holland +4

Magnetic resonance imaging (MRI) is an invaluable tool for clinical and research applications. Yet, variations in scanners and acquisition parameters cause inconsistencies in image…

eess.IV2025

VIBESegmentator: Full Body MRI Segmentation for the NAKO and UK Biobank

Robert Graf, Paul-Sören Platzek, Evamaria Olga Riedel +17

Objectives: To present a publicly available deep learning-based torso segmentation model that provides comprehensive voxel-wise coverage, including delineations that extend to the…