Rickmer Braren
Orcid: 0000-0001-6039-6957
According to our database1,
Rickmer Braren
authored at least 50 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations.
Trans. Mach. Learn. Res., 2024
Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution.
CoRR, 2024
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain.
CoRR, 2024
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation.
CoRR, 2024
Proceedings of the Biomedical Image Registration - 11th International Workshop, 2024
Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Segmentation-guided Medical Image Registration - Quality Awareness using Label Noise Correctionn.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024
2023
CoRR, 2023
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology.
CoRR, 2023
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans.
IEEE Access, 2023
Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the Shape in Medical Imaging - International Workshop, 2023
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023
3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Exploiting Segmentation Labels and Representation Learning to Forecast Therapy Response of PDAC Patients.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Abstract: Deep-learning on Lossily Compressed Pathology Images - Adverse Effects for ImageNet Pre-trained Models.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023
2022
Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study.
npj Digit. Medicine, 2022
CoRR, 2022
Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models.
Proceedings of the Medical Optical Imaging and Virtual Microscopy Image Analysis, 2022
DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022
Longitudinal Analysis of Disease Progression Using Image and Laboratory Data for Covid-19 Patients.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022
2021
Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study.
npj Digit. Medicine, 2021
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning.
Nat. Mach. Intell., 2021
Nat. Mach. Intell., 2021
CoRR, 2021
Differentially private training of neural networks with Langevin dynamics forcalibrated predictive uncertainty.
CoRR, 2021
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation.
CoRR, 2021
Differentially private federated deep learning for multi-site medical image segmentation.
CoRR, 2021
A Computed Tomography Vertebral Segmentation Dataset with Anatomical Variations and Multi-Vendor Scanner Data.
CoRR, 2021
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Segmentation of Peripancreatic Arteries in Multispectral Computed Tomography Imaging.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021
2020
Nat. Mach. Intell., 2020
Efficient, high-performance pancreatic segmentation using multi-scale feature extraction.
CoRR, 2020
2019
Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
Differential Diagnosis for Pancreatic Cysts in CT Scans Using Densely-Connected Convolutional Networks.
CoRR, 2018
2017
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks.
CoRR, 2017
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D Convolutional Neural Networks.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017