19 citations · 30 across the 28 of their papers we have counts for
29 papers
Bridging Modalities on the Cortex: Surface-based MRI to PET Translation with a Diffusion Bridge
Yitong Li, Alexandra Samoylova, Fabian Bongratz +4
Cortical hypometabolism measured by Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is a highly sensitive biomarker for dementia diagnosis. However, high costs, radiation…
International Transfer of Stochastic Cortical Self-Reconstruction
Fabian Bongratz, Zhizheng Zhuo, Chao Zhang +3
Stochastic cortical self-reconstruction (SCSR) enables personalized mapping of gray matter atrophy, a hallmark of neurodegenerative disorders such as Alzheimer's disease (AD), onto…
Routine laboratory trajectories encode the onset of organ-level complications in cancer
Jannik Lübberstedt, Krischan Braitsch, Jacqueline Lammert +21
Routine laboratory panels drawn during cancer treatment constitute longitudinal physiological recordings of organ function, yet their temporal structure is discarded by single-time…
Whole-body CT attenuation and volume charts from routine clinical scans via evidence-grounded LLM report filtering
Christian Wachinger, Bernhard Renger, Christopher Späth +2
Interpreting quantitative CT biomarkers, such as organ volume and tissue attenuation, requires large-scale healthy reference distributions. However, creating these is challenging b…
Translating MRI to PET through Conditional Diffusion Models with Enhanced Pathology Awareness
Yitong Li, Igor Yakushev, Dennis M. Hedderich +1
Positron emission tomography (PET) is a widely recognized technique for diagnosing neurodegenerative diseases, offering critical functional insights. However, its high costs and ra…
Conditional Diffusion for 3D CT Volume Reconstruction from 2D X-rays
Martin Rath, Morteza Ghahremani, Yitong Li +3
Computed tomography (CT) provides rich 3D anatomical detail but is often constrained by high radiation exposure, substantial costs, and limited availability. Standard chest X-rays…
Cortex-Grounded Diffusion Models for Brain Image Generation
Fabian Bongratz, Yitong Li, Sama Elbaroudy +1
Synthetic neuroimaging data can mitigate critical limitations of real-world datasets, including the scarcity of rare phenotypes, domain shifts across scanners, and insufficient lon…
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…
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…
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…
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…
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…
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…
Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging
Yitong Li, Morteza Ghahremani, Christian Wachinger
Vision-language foundation models achieve promising performance in natural image classification, yet their direct application to medical imaging is limited by severe domain shifts,…
3D Shape-to-Image Brownian Bridge Diffusion for Brain MRI Synthesis from Cortical Surfaces
Fabian Bongratz, Yitong Li, Sama Elbaroudy +1
Despite recent advances in medical image generation, existing methods struggle to produce anatomically plausible 3D structures. In synthetic brain magnetic resonance images (MRIs),…
SIC: Similarity-Based Interpretable Image Classification with Neural Networks
Tom Nuno Wolf, Emre Kavak, Fabian Bongratz +1
The deployment of deep learning models in critical domains necessitates a balance between high accuracy and interpretability. We introduce SIC, an inherently interpretable neural n…
TimeFlow: Temporal Conditioning for Longitudinal Brain MRI Registration and Aging Analysis
Bailiang Jian, Jiazhen Pan, Yitong Li +5
Longitudinal brain analysis is essential for understanding healthy aging and identifying pathological deviations. Longitudinal registration of sequential brain MRI underpins such a…
MLV-Net: Rater-Based Majority-Label Voting for Consistent Meningeal Lymphatic Vessel Segmentation
Fabian Bongratz, Markus Karmann, Adrian Holz +9
Meningeal lymphatic vessels (MLVs) are responsible for the drainage of waste products from the human brain. An impairment in their functionality has been associated with aging as w…
DiaMond: Dementia Diagnosis with Multi-Modal Vision Transformers Using MRI and PET
Yitong Li, Morteza Ghahremani, Youssef Wally +1
Diagnosing dementia, particularly for Alzheimer's Disease (AD) and frontotemporal dementia (FTD), is complex due to overlapping symptoms. While magnetic resonance imaging (MRI) and…
Mamba? Catch The Hype Or Rethink What Really Helps for Image Registration
Bailiang Jian, Jiazhen Pan, Morteza Ghahremani +3
Our findings indicate that adopting "advanced" computational elements fails to significantly improve registration accuracy. Instead, well-established registration-specific designs…
Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation
Jiajun Wang, Morteza Ghahremani, Yitong Li +2
Controllable text-to-image (T2I) diffusion models have shown impressive performance in generating high-quality visual content through the incorporation of various conditions. Curre…
PASTA: Pathology-Aware MRI to PET Cross-Modal Translation with Diffusion Models
Yitong Li, Igor Yakushev, Dennis M. Hedderich +1
Positron emission tomography (PET) is a well-established functional imaging technique for diagnosing brain disorders. However, PET's high costs and radiation exposure limit its wid…
From Barlow Twins to Triplet Training: Differentiating Dementia with Limited Data
Yitong Li, Tom Nuno Wolf, Sebastian Pölsterl +3
Differential diagnosis of dementia is challenging due to overlapping symptoms, with structural magnetic resonance imaging (MRI) being the primary method for diagnosis. Despite the…
Individualized Mapping of Aberrant Cortical Thickness via Stochastic Cortical Self-Reconstruction
Christian Wachinger, Dennis Hedderich, Melissa Thalhammer +1
Understanding individual differences in cortical structure is key to advancing diagnostics in neurology and psychiatry. Reference models aid in detecting aberrant cortical thicknes…