most citedAdvances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge

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cs.CV2026

Anguinus Sculpturae: Compositional Synthesis of Peak-Enhancement Breast DCE-MRI Scans

Benjamin Hamm, Nico Albert Disch, Maximilian Rokuss +3

Dynamic contrast-enhanced breast MRI (DCE-MRI) is rich in anatomical and perfusion information, but its reliance on gadolinium-based contrast agents raises safety concerns and adds…

cs.CV2026

Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking

Yannick Kirchhoff, Maximilian Rokuss, Daniel Philipp Mertens +5

Tracking tumor lesions across serial CT scans is essential for oncological response assessment. Existing automated methods face a fundamental trade-off: end-to-end trackers achieve…

cs.CV2026

Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge

Asbjørn Munk, Stefano Cerri, Vardan Nersesjan +81

Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are prohibitively costly to obt…

cs.CV2026

TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT

Marawan Elbatel, Mohamed Ghonim, Jiaji Mao +62

Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly in low-resource settings acro…

cs.CV2025

CRONOS: Continuous Time Reconstruction for 4D Medical Longitudinal Series

Nico Albert Disch, Saikat Roy, Constantin Ulrich +5

Forecasting how 3D medical scans evolve over time is important for disease progression, treatment planning, and developmental assessment. Yet existing models either rely on a singl…

cs.CV2025

MeisenMeister: A Simple Two Stage Pipeline for Breast Cancer Classification on MRI

Benjamin Hamm, Yannick Kirchhoff, Maximilian Rokuss +1

The ODELIA Breast MRI Challenge 2025 addresses a critical issue in breast cancer screening: improving early detection through more efficient and accurate interpretation of breast M…

cs.CV2025★ 4 cited

Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge

Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67

Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…