1 citations · 2 across the 16 of their papers we have counts for
17 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…
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…
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…
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…
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),…
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…
How to Choose a Reinforcement-Learning Algorithm
Fabian Bongratz, Vladimir Golkov, Lukas Mautner +5
The field of reinforcement learning offers a large variety of concepts and methods to tackle sequential decision-making problems. This variety has become so large that choosing an…
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…
V2C-Long: Longitudinal Cortex Reconstruction with Spatiotemporal Correspondence
Fabian Bongratz, Jan Fecht, Anne-Marie Rickmann +1
Reconstructing the cortex from longitudinal magnetic resonance imaging (MRI) is indispensable for analyzing morphological alterations in the human brain. Despite the recent advance…
Neural deformation fields for template-based reconstruction of cortical surfaces from MRI
Fabian Bongratz, Anne-Marie Rickmann, Christian Wachinger
The reconstruction of cortical surfaces is a prerequisite for quantitative analyses of the cerebral cortex in magnetic resonance imaging (MRI). Existing segmentation-based methods…
Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning
Tom Nuno Wolf, Fabian Bongratz, Anne-Marie Rickmann +2
Explaining predictions of black-box neural networks is crucial when applied to decision-critical tasks. Thus, attribution maps are commonly used to identify important image regions…
Abdominal organ segmentation via deep diffeomorphic mesh deformations
Fabian Bongratz, Anne-Marie Rickmann, Christian Wachinger
Abdominal organ segmentation from CT and MRI is an essential prerequisite for surgical planning and computer-aided navigation systems. It is challenging due to the high variability…
Joint Reconstruction and Parcellation of Cortical Surfaces
Anne-Marie Rickmann, Fabian Bongratz, Sebastian Pölsterl +2
The reconstruction of cerebral cortex surfaces from brain MRI scans is instrumental for the analysis of brain morphology and the detection of cortical thinning in neurodegenerative…
Vox2Cortex: Fast Explicit Reconstruction of Cortical Surfaces from 3D MRI Scans with Geometric Deep Neural Networks
Fabian Bongratz, Anne-Marie Rickmann, Sebastian Pölsterl +1
The reconstruction of cortical surfaces from brain magnetic resonance imaging (MRI) scans is essential for quantitative analyses of cortical thickness and sulcal morphology. Althou…