Benedikt Wiestler
Orcid: 0000-0002-2963-7772
According to our database1,
Benedikt Wiestler
authored at least 97 papers
between 2015 and 2024.
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Bibliography
2024
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
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
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
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge.
CoRR, 2024
Proceedings of the Biomedical Image Registration - 11th International Workshop, 2024
Proceedings of the Deep Generative Models - 4th MICCAI Workshop, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Simulation and Synthesis in Medical Imaging, 2024
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
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
CoRR, 2023
Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans.
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
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
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
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Proceedings of the Information Processing in Medical Imaging, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023
2022
IEEE Trans. Medical Imaging, 2022
Federated disentangled representation learning for unsupervised brain anomaly detection.
Nat. Mach. Intell., 2022
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
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
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, 2022
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
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
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation.
CoRR, 2021
Comput. Medical Imaging Graph., 2021
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
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021
2020
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
Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020
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
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
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