Holger Roth

Orcid: 0000-0002-3662-8743

According to our database1, Holger Roth authored at least 145 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

Empowering Federated Learning for Massive Models with NVIDIA FLARE.
CoRR, 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

Do Gradient Inversion Attacks Make Federated Learning Unsafe?
IEEE Trans. Medical Imaging, 2023

NVIDIA FLARE: Federated Learning from Simulation to Real-World.
IEEE Data Eng. Bull., 2023

FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models.
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, 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

Fair Federated Medical Image Segmentation via Client Contribution Estimation.
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

MONAI: An open-source framework for deep learning in healthcare.
CoRR, 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

MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images.
CoRR, 2022

A cascaded fully convolutional network framework for dilated pancreatic duct segmentation.
Int. J. Comput. Assist. Radiol. Surg., 2022

UNETR: Transformers for 3D Medical Image Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Effective hyperparameter optimization with proxy data for multi-organ segmentation.
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

DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images.
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

Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

GradViT: Gradient Inversion of Vision Transformers.
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

Going to Extremes: Weakly Supervised Medical Image Segmentation.
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

UNETR: Transformers for 3D 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

Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures.
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

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation.
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

Attention-Guided Pancreatic Duct Segmentation from Abdominal CT Volumes.
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

The future of digital health with federated learning.
npj Digit. Medicine, 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

Learning Image Labels On-the-fly for Training Robust Classification Models.
CoRR, 2020

Enhancing Foreground Boundaries for Medical Image Segmentation.
CoRR, 2020

NeurReg: Neural Registration and Its Application to Image Segmentation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training.
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

LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation.
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


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

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation.
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

When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation.
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

Improving V-Nets for multi-class abdominal organ segmentation.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Colonoscope tracking method based on shape estimation network.
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

Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks.
Proceedings of the Graph Learning in Medical Imaging - First International Workshop, 2019

Weakly Supervised Segmentation from Extreme Points.
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

Cardiac Segmentation of LGE MRI with Noisy Labels.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, 2019

4D CNN for Semantic Segmentation of Cardiac Volumetric Sequences.
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

End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Weakly-supervised deep learning of interstitial lung disease types on CT images.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

Lung segmentation based on a deep learning approach for dynamic chest radiography.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

Polyp-size classification with RGB-D features for colonoscopy.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 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

Deep learning and its application to medical image segmentation.
CoRR, 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

An analysis of robust cost functions for CNN in computer-aided diagnosis.
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

BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images.
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

Automatic Pancreas Segmentation Using Coarse-to-Fine Superpixel Labeling.
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

Hierarchical 3D fully convolutional networks for multi-organ segmentation.
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

TBS: Tensor-Based Supervoxels for Unfolding the Heart.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Micro-CT Guided 3D Reconstruction of Histological Images.
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

Automatic segmentation of head anatomical structures from sparsely-annotated images.
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

Improving vertebra segmentation through joint vertebra-rib atlases.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 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, California, United States, 27 February, 2016

2015
Deep convolutional networks for pancreas segmentation in CT imaging.
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

Leveraging Mid-Level Semantic Boundary Cues for Automated Lymph Node Detection.
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

Anatomy-specific classification of medical images using deep convolutional nets.
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
Endoluminal surface registration for CT colonography using haustral fold matching.
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

Registration of Temporally Separated CT Colonography Cases.
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
External Clinical Validation of Prone and Supine CT Colonography Registration.
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


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