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20232026
most citedPASTA: Pathology-Aware MRI to PET Cross-Modal Translation with Diffusion Models

19 citations · 30 across the 28 of their papers we have counts for

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Showing 2025Show all

10 papers · 1 filter

cs.CV2025

Diffusion Bridge Networks Simulate Clinical-grade PET from MRI for Dementia Diagnostics

Yitong Li, Ralph Buchert, Benita Schmitz-Koep +5

Positron emission tomography (PET) with 18F-Fluorodeoxyglucose (FDG) is an established tool in the diagnostic workup of patients with suspected dementing disorders. However, compar…

cs.CV2025

Template-Based Cortical Surface Reconstruction with Minimal Energy Deformation

Patrick Madlindl, Fabian Bongratz, Christian Wachinger

Cortical surface reconstruction (CSR) from magnetic resonance imaging (MRI) is fundamental to neuroimage analysis, enabling morphological studies of the cerebral cortex and functio…

cs.CV2025

Spherical Brownian Bridge Diffusion Models for Conditional Cortical Thickness Forecasting

Ivan Stoyanov, Fabian Bongratz, Christian Wachinger

Accurate forecasting of individualized, high-resolution cortical thickness (CTh) trajectories is essential for detecting subtle cortical changes, providing invaluable insights into…

cs.LG2025★ 2 cited

Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming

Jiazhen Pan, Bailiang Jian, Paul Hager +19

Large language models (LLMs) are increasingly used to answer health-related questions and support healthcare workflows, yet evidence for their safety still relies heavily on static…

cs.GR2025

X-SiT: Inherently Interpretable Surface Vision Transformers for Dementia Diagnosis

Fabian Bongratz, Tom Nuno Wolf, Jaume Gual Ramon +1

Interpretable models are crucial for supporting clinical decision-making, driving advances in their development and application for medical images. However, the nature of 3D volume…

cs.CV2025

DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation

Emre Kavak, Tom Nuno Wolf, Christian Wachinger

Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Anti-Causal Model (SAM), a unifying causa…