Holger Roth
Orcid: 0000-0002-3662-8743
According to our database1,
Holger Roth
authored at least 161 papers
between 2010 and 2024.
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Bibliography
2024
Deep Learning-based Diagnosis and Localization of Pneumothorax on Portable Supine Chest X-ray in Intensive and Emergency Medicine: A Retrospective Study.
J. Medical Syst., December, 2024
Anatomical attention can help to segment the dilated pancreatic duct in abdominal CT.
Int. J. Comput. Assist. Radiol. Surg., April, 2024
Patterns, 2024
Fair evaluation of federated learning algorithms for automated breast density classification: The results of the 2022 ACR-NCI-NVIDIA federated learning challenge.
Medical Image Anal., 2024
Medical Image Anal., 2024
HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization.
CoRR, 2024
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions.
CoRR, 2024
Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge.
CoRR, 2024
Federated Learning Privacy: Attacks, Defenses, Applications, and Policy Landscape - A Survey.
CoRR, 2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
IR-FRestormer: Iterative Refinement with Fourier-Based Restormer for Accelerated MRI Reconstruction.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024
Super-Field MRI Synthesis for Infant Brains Enhanced by Dual Channel Latent Diffusion.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
D-Rax: Domain-Specific Radiologic Assistant Leveraging Multi-modal Data and eXpert Model Predictions.
Proceedings of the Foundation Models for General Medical AI, 2024
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
Accelerating artificial intelligence: How federated learning can protect privacy, facilitate collaboration, and improve outcomes.
Health Informatics J., October, 2023
Guest Editorial Special Issue on Federated Learning for Medical Imaging: Enabling Collaborative Development of Robust AI Models.
IEEE Trans. Medical Imaging, 2023
IEEE Trans. Medical Imaging, 2023
IEEE Data Eng. Bull., 2023
CoRR, 2023
Semi-supervised Learning with Contrastive and Topology Losses for Catheter Segmentation and Misplacement Prediction.
Proceedings of the Medical Imaging with Deep Learning, 2023
DAST: Differentiable Architecture Search with Transformer for 3D Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
ConDistFL: Conditional Distillation for Federated Learning from Partially Annotated Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
From adult to pediatric: deep learning-based automatic segmentation of rare pediatric brain tumors.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
Automatic Segmentation of Rare Pediatric Brain Tumors Using Knowledge Transfer From Adult Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Automatic Visual Acuity Loss Prediction in Children with Optic Pathway Gliomas using Magnetic Resonance Imaging.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge.
Medical Image Anal., 2022
Rapid artificial intelligence solutions in a pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge.
Medical Image Anal., 2022
Warm Start Active Learning with Proxy Labels & Selection via Semi-Supervised Fine-Tuning.
CoRR, 2022
UNetFormer: A Unified Vision Transformer Model and Pre-Training Framework for 3D Medical Image Segmentation.
CoRR, 2022
CoRR, 2022
A cascaded fully convolutional network framework for dilated pancreatic duct segmentation.
Int. J. Comput. Assist. Radiol. Surg., 2022
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Clinical-Realistic Annotation for Histopathology Images with Probabilistic Semi-supervision: A Worst-Case Study.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Joint Multi Organ and Tumor Segmentation from Partial Labels Using Federated Learning.
Proceedings of the Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health, 2022
Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-modal Brain Tumor Segmentation.
Proceedings of the Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health, 2022
Warm Start Active Learning with Proxy Labels and Selection via Semi-supervised Fine-Tuning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the Data Augmentation, Labelling, and Imperfections, 2022
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation.
Proceedings of the Computer Vision - ECCV 2022, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
Guest Editorial Annotation-Efficient Deep Learning: The Holy Grail of Medical Imaging.
IEEE Trans. Medical Imaging, 2021
Diminishing Uncertainty Within the Training Pool: Active Learning for Medical Image Segmentation.
IEEE Trans. Medical Imaging, 2021
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan.
Medical Image Anal., 2021
Mach. Learn. Knowl. Extr., 2021
Federated learning improves site performance in multicenter deep learning without data sharing.
J. Am. Medical Informatics Assoc., 2021
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation.
CoRR, 2021
Detection and Classification of Coronary Artery Plaques in Coronary Computed Tomography Angiography Using 3D CNN.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
The Power of Proxy Data and Proxy Networks for Hyper-parameter Optimization in Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Accounting for Dependencies in Deep Learning Based Multiple Instance Learning for Whole Slide Imaging.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021
Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2021
2020
Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation.
IEEE Trans. Medical Imaging, 2020
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation.
Medical Image Anal., 2020
Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning.
CoRR, 2020
CoRR, 2020
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020
Spatial information-embedded fully convolutional networks for multi-organ segmentation with improved data augmentation and instance normalization.
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Correlation via Synthesis: End-to-end Image Generation and Radiogenomic Learning Based on Generative Adversarial Network.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning.
Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020
Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020
Usefulness of fine-tuning for deep learning based multi-organ regions segmentation method from non-contrast CT volumes using small training dataset.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2019
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network.
CoRR, 2019
CoRR, 2019
Interactive segmentation of medical images through fully convolutional neural networks.
CoRR, 2019
Precise estimation of renal vascular dominant regions using spatially aware fully convolutional networks, tensor-cut and Voronoi diagrams.
Comput. Medical Imaging Graph., 2019
Abdominal artery segmentation method from CT volumes using fully convolutional neural network.
Int. J. Comput. Assist. Radiol. Surg., 2019
Proceedings of the Medical Imaging 2019: Image Processing, 2019
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Tunable CT Lung Nodule Synthesis Conditioned on Background Image and Semantic Features.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2019
Proceedings of the Graph Learning in Medical Imaging - First International Workshop, 2019
Proceedings of the Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, 2019
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, 2019
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, 2019
Unsupervised Segmentation of Micro-CT Images of Lung Cancer Specimen Using Deep Generative Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Scanning, registration, and fiber estimation of rabbit hearts using micro-focus and refraction-contrast x-ray CT.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019
Unsupervised segmentation of micro-CT images based on a hybrid of variational inference and adversarial learning.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019
2018
Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.
Medical Image Anal., 2018
On the influence of Dice loss function in multi-class organ segmentation of abdominal CT using 3D fully convolutional networks.
CoRR, 2018
An application of cascaded 3D fully convolutional networks for medical image segmentation.
Comput. Medical Imaging Graph., 2018
Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2018
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2018
Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks.
Proceedings of the Medical Imaging 2018: Image Processing, 2018
Unsupervised pathology image segmentation using representation learning with spherical k-means.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
Fully Convolutional Network-Based Eyeball Segmentation from Sparse Annotation for Eye Surgery Simulation Model.
Proceedings of the Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation, 2018
A Multi-scale Pyramid of 3D Fully Convolutional Networks for Abdominal Multi-organ Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Colon Shape Estimation Method for Colonoscope Tracking Using Recurrent Neural Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Towards Automated Colonoscopy Diagnosis: Binary Polyp Size Estimation via Unsupervised Depth Learning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Automatic segmentation of eyeball structures from micro-CT images based on sparse annotation.
Proceedings of the Medical Imaging 2018: Biomedical Applications in Molecular, 2018
Unsupervised segmentation of 3D medical images based on clustering and deep representation learning.
Proceedings of the Medical Imaging 2018: Biomedical Applications in Molecular, 2018
2017
Three Aspects on Using Convolutional Neural Networks for Computer-Aided Detection in Medical Imaging.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017
Efficient False Positive Reduction in Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017
A Bottom-Up Approach for Pancreas Segmentation Using Cascaded Superpixels and (Deep) Image Patch Labeling.
IEEE Trans. Image Process., 2017
Towards Automatic Abdominal Multi-Organ Segmentation in Dual Energy CT using Cascaded 3D Fully Convolutional Network.
CoRR, 2017
CoRR, 2017
Multi-scale Image Fusion Between Pre-operative Clinical CT and X-ray Microtomography of Lung Pathology.
CoRR, 2017
Comparison of the deep-learning-based automated segmentation methods for the head sectioned images of the virtual Korean human project.
Proceedings of the Fifteenth IAPR International Conference on Machine Vision Applications, 2017
Automatic MR prostate segmentation by deep learning with holistically-nested networks.
Proceedings of the Medical Imaging 2017: Image Processing, 2017
Motion Vector for Outlier Elimination in Feature Matching and Its Application in SLAM Based Laparoscopic Tracking.
Proceedings of the Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures, 2017
3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Proceedings of the Patch-Based Techniques in Medical Imaging, 2017
Tracking and Segmentation of the Airways in Chest CT Using a Fully Convolutional Network.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Deep learning with orthogonal volumetric HED segmentation and 3D surface reconstruction model of prostate MRI.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Proceedings of the IEEE International Conference on Cyborg and Bionic Systems, 2017
2016
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.
IEEE Trans. Medical Imaging, 2016
Improving Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation.
IEEE Trans. Medical Imaging, 2016
Active appearance model and deep learning for more accurate prostate segmentation on MRI.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Spatial Aggregation of Holistically-Nested Networks for Automated Pancreas Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Automatic Lymph Node Cluster Segmentation Using Holistically-Nested Neural Networks and Structured Optimization in CT Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Deep convolutional networks for automated detection of posterior-element fractures on spine CT.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
2015
Proceedings of the Medical Imaging 2015: Image Processing, 2015
Multi-atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT.
Proceedings of the Computational Methods and Clinical Applications for Spine Imaging, 2015
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015
DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015
2014
Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications.
CoRR, 2014
Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study.
Proceedings of the Medical Imaging 2014: Image-Guided Procedures, 2014
2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
2013
Medical Image Anal., 2013
CT colonography: inverse-consistent symmetric registration of prone and supine inner colon surfaces.
Proceedings of the Medical Imaging 2013: Image Processing, 2013
Registration of Prone and Supine CT Colonography Datasets with Differing Endoluminal Distension.
Proceedings of the Abdominal Imaging. Computation and Clinical Applications, 2013
Proceedings of the Abdominal Imaging. Computation and Clinical Applications, 2013
Spatial Correspondence between Prone and Supine CT Colonography Images: Creating a Reference Standard.
Proceedings of the Abdominal Imaging. Computation and Clinical Applications, 2013
2012
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2012
Prone to Supine CT Colonography Registration Using a Landmark and Intensity Composite Method.
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2012
Establishing spatial correspondence for the analysis of images from highly deforming anatomy.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012
2011
Inverse Consistency Error in the Registration of Prone and Supine Images in CT Colonography.
Proceedings of the Abdominal Imaging. Computational and Clinical Applications, 2011
Automatic Prone to Supine Haustral Fold Matching in CT Colonography Using a Markov Random Field Model.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011
2010
Establishing Spatial Correspondence between the Inner Colon Surfaces from Prone and Supine CT Colonography.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010