Benedikt Wiestler

Orcid: 0000-0002-2963-7772

According to our database1, Benedikt Wiestler authored at least 97 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Framework for Multimodal Medical Image Interaction.
IEEE Trans. Vis. Comput. Graph., November, 2024

<i>Where is VALDO?</i> VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.
Medical Image Anal., January, 2024

Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization.
CoRR, 2024

Learning Brain Tumor Representation in 3D High-Resolution MR Images via Interpretable State Space Models.
CoRR, 2024

ISLES 2024: The first longitudinal multimodal multi-center real-world dataset in (sub-)acute stroke.
CoRR, 2024

ISLES'24: Improving final infarct prediction in ischemic stroke using multimodal imaging and clinical data.
CoRR, 2024

Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder.
CoRR, 2024

BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023.
CoRR, 2024

Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders.
CoRR, 2024

TotalVibeSegmentator: Full Torso Segmentation for the NAKO and UK Biobank in Volumetric Interpolated Breath-hold Examination Body Images.
CoRR, 2024

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge.
CoRR, 2024

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation.
CoRR, 2024

The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI.
CoRR, 2024

The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).
CoRR, 2024

Multi-Image Visual Question Answering for Unsupervised Anomaly Detection.
CoRR, 2024

A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge.
CoRR, 2024

A Learnable Prior Improves Inverse Tumor Growth Modeling.
CoRR, 2024

Towards Universal Unsupervised Anomaly Detection in Medical Imaging.
CoRR, 2024

Mamba? Catch The Hype Or Rethink What Really Helps for Image Registration.
Proceedings of the Biomedical Image Registration - 11th International Workshop, 2024


Diffusion Models with Implicit Guidance for Medical Anomaly Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

MedEdit: Counterfactual Diffusion-Based Image Editing on Brain MRI.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2024

H-ViT: A Hierarchical Vision Transformer for Deformable Image Registration.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling.
Medical Image Anal., 2023

The Liver Tumor Segmentation Benchmark (LiTS).
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Medical Image Anal., 2023

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA.
CoRR, 2023

Individualizing Glioma Radiotherapy Planning by Optimization of a Data and Physics Informed Discrete Loss.
CoRR, 2023

Panoptica - instance-wise evaluation of 3D semantic and instance segmentation maps.
CoRR, 2023

Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans.
CoRR, 2023

(Predictable) Performance Bias in Unsupervised Anomaly Detection.
CoRR, 2023

Denoising diffusion-based MR to CT image translation enables whole spine vertebral segmentation in 2D and 3D without manual annotations.
CoRR, 2023

Framing image registration as a landmark detection problem for better representation of clinical relevance.
CoRR, 2023

Inter-Rater Uncertainty Quantification in Medical Image Segmentation via Rater-Specific Bayesian Neural Networks.
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).
CoRR, 2023

The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting.
CoRR, 2023

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.
CoRR, 2023

Primitive Simultaneous Optimization of Similarity Metrics for Image Registration.
CoRR, 2023

Multi-contrast MRI Super-resolution via Implicit Neural Representations.
CoRR, 2023

Semantic Latent Space Regression of Diffusion Autoencoders for Vertebral Fracture Grading.
CoRR, 2023

ViT-AE++: Improving Vision Transformer Autoencoder for Self-supervised Medical Image Representations.
Proceedings of the Medical Imaging with Deep Learning, 2023

Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening.
Proceedings of the Medical Imaging with Deep Learning, 2023

Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Multimodal Context-Aware Detection of Glioma Biomarkers Using MRI and WSI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

Metrics to Quantify Global Consistency in Synthetic Medical Images.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023


blob loss: Instance Imbalance Aware Loss Functions for Semantic Segmentation.
Proceedings of the Information Processing in Medical Imaging, 2023

Why is the Winner the Best?
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Bias in Unsupervised Anomaly Detection in Brain MRI.
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023

2022
Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor Models.
IEEE Trans. Medical Imaging, 2022

Federated disentangled representation learning for unsupervised brain anomaly detection.
Nat. Mach. Intell., 2022

ROAM: Random layer mixup for semi-supervised learning in medical images.
IET Image Process., 2022

A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images.
CoRR, 2022

Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.
CoRR, 2022

CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN.
CoRR, 2022

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.
CoRR, 2022

Casting the inverse problem as a database query. The case of personalized tumor growth modeling.
CoRR, 2022

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling.
Proceedings of the Machine Learning for Health, 2022

On the Pitfalls of Using the Residual Error as Anomaly Score.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Interpretable Vertebral Fracture Diagnosis.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, 2022

Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022

2021
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.
Medical Image Anal., 2021

Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study.
Medical Image Anal., 2021

The Brain Tumor Sequence Registration Challenge: Establishing Correspondence between Pre-Operative and Follow-up MRI scans of diffuse glioma patients.
CoRR, 2021

FedCostWAvg: A new averaging for better Federated Learning.
CoRR, 2021

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification.
CoRR, 2021

A Computed Tomography Vertebral Segmentation Dataset with Anatomical Variations and Multi-Vendor Scanner Data.
CoRR, 2021

Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient.
CoRR, 2021

Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations.
CoRR, 2021

FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation.
CoRR, 2021

Analyzing magnetic resonance imaging data from glioma patients using deep learning.
Comput. Medical Imaging Graph., 2021

Imbalance-Aware Self-supervised Learning for 3D Radiomic Representations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Unpaired MR Image Homogenisation by Disentangled Representations and Its Uncertainty.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis, 2021

FedCostWAvg: A New Averaging for Better Federated Learning.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021

2020
Real-time Bayesian personalization via a learnable brain tumor growth model.
CoRR, 2020

Train, Learn, Expand, Repeat.
CoRR, 2020

e-UDA: Efficient Unsupervised Domain Adaptation for Cross-Site Medical Image Segmentation.
CoRR, 2020

VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images.
CoRR, 2020

Reinforced Redetection of Landmark in Pre- and Post-operative Brain Scan Using Anatomical Guidance for Image Alignment.
Proceedings of the Biomedical Image Registration - 9th International Workshop, 2020

Reliable Saliency Maps for Weakly-Supervised Localization of Disease Patterns.
Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020

Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

SteGANomaly: Inhibiting CycleGAN Steganography for Unsupervised Anomaly Detection in Brain MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Bayesian Skip-Autoencoders for Unsupervised Hyperintense Anomaly Detection in High Resolution Brain Mri.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference.
IEEE Trans. Medical Imaging, 2019

Fusing Unsupervised and Supervised Deep Learning for White Matter Lesion Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Graph Convolution Based Attention Model for Personalized Disease Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.
CoRR, 2018

Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration.
CoRR, 2018

Deep Learning with Synthetic Diffusion MRI Data for Free-Water Elimination in Glioblastoma Cases.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

2017
Multi-modal Image Classification Using Low-Dimensional Texture Features for Genomic Brain Tumor Recognition.
Proceedings of the Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017

2015
Relaxation-compensated CEST-MRI of the human brain at 7 T: Unbiased insight into NOE and amide signal changes in human glioblastoma.
NeuroImage, 2015


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