Fabian Isensee

Gabriel Efrain Humpire Mamani

Medical Image Anal., May, 2023

The Liver Tumor Segmentation Benchmark (LiTS).

[BibT_eX]

[DOI]

Patrick Bilic

Patrick Ferdinand Christ

Michal Marianne Amitai

Krishna Chaitanya Kaluva

Tomasz K. Konopczynski

Avinash Kori

Ganapathy Krishnamurthi

Kevis-Kokitsi Maninis

Medical Image Anal., 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

Look Ma, no code: fine tuning nnU-Net for the AutoPET II challenge by only adjusting its JSON plans.

[BibT_eX]

[DOI]

CoRR, 2023

Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency.

[BibT_eX]

[DOI]

CoRR, 2023

The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CT.

[BibT_eX]

[DOI]

CoRR, 2023

Transformer Utilization in Medical Image Segmentation Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Why is the winner the best?

[BibT_eX]

[DOI]

CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.

[BibT_eX]

[DOI]

Doreen Heckmann-Nötzel

Evangelia Christodoulou

Alexandros Karargyris

Alan Karthikesalingam

Sotirios A. Tsaftaris

CoRR, 2023

[Work in progress] Scalable, out-of-the box segmentation of individual particles from mineral samples acquired with micro CT.

[BibT_eX]

[DOI]

Karol Gotkowski

Shuvam Gupta

Jose R. A. Godinho

Camila G. S. Tochtrop

Kimberlin M. H. van Wijnen

CoRR, 2023

CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization.

[BibT_eX]

[DOI]

CoRR, 2023

MultiTalent: A Multi-dataset Approach to Medical Image Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

MedNeXt: Transformer-Driven Scaling of ConvNets for Medical Image Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Anatomy-Informed Data Augmentation for Enhanced Prostate Cancer Detection.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Why is the Winner the Best?

[BibT_eX]

[DOI]

Matthias Eisenmann

Annika Reinke

Vivienn Weru

Minu Dietlinde Tizabi

Jonathan Rafael-Patino

Vivek Singh Bawa

Stefanie Speidel

Carole H. Sudre

Christoph M. Friedrich

Maria Grammatikopoulou

S. Hong

Mostafa Jahanifar

I. Jang

Abdolrahim Kadkhodamohammadi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Abstract: MOOD 2020 - A Public Benchmark for Out-of-distribution Detection and Localization on Medical Images.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Abstract: Automated Detection and Quantification of Brain Metastases on Clinical MRI Data using CNNs.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Contrastive Representations for Unsupervised Anomaly Detection and Localization.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

Extending nnU-Net Is All You Need.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022

MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2022

Rapid artificial intelligence solutions in a pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge.

[BibT_eX]

[DOI]

Medical Image Anal., 2022

Biomedical image analysis competitions: The state of current participation practice.

[BibT_eX]

[DOI]

CoRR, 2022

Evaluation of Medical Image Segmentation Models for Uncertain, Small or Empty Reference Annotations.

[BibT_eX]

[DOI]

CoRR, 2022

Metrics reloaded: Pitfalls and recommendations for image analysis validation.

[BibT_eX]

[DOI]

Annika Reinke

Evangelia Christodoulou

Doreen Heckmann-Nötzel

A. Emre Kavur

Tim Rädsch

Minu Dietlinde Tizabi

Alexandros Karargyris

Alan Karthikesalingam

Hannes Kenngott

Clarisa Sánchez Gutiérrez

Sotirios A. Tsaftaris

Ben Van Calster

Gaël Varoquaux

Paul F. Jäger

CoRR, 2022

Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads.

[BibT_eX]

[DOI]

Leon Pascal Schuhmacher

Proceedings of the High Performance Computing. ISC High Performance 2022 International Workshops - Hamburg, Germany, May 29, 2022

A Noisy nnU-Net Student for Semi-supervised Abdominal Organ Segmentation.

[BibT_eX]

[DOI]

Gregor Köhler

Proceedings of the Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation, 2022

Heterogeneous Model Ensemble For Automatic Polyp Segmentation In Endoscopic Video Sequences.

[BibT_eX]

[DOI]

Proceedings of the 4th International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2022) co-located with the 19th IEEE International Symposium on Biomedical Imaging (ISBI 2022), 2022

Realistic Evaluation of FixMatch on Imbalanced Medical Image Classification Tasks.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Abstract: nnDetection - A Self-configuring Method for Medical Object Detection.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021

Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge.

[BibT_eX]

[DOI]

Medical Image Anal., 2021

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

[BibT_eX]

[DOI]

Medical Image Anal., 2021

The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge.

[BibT_eX]

[DOI]

Medical Image Anal., 2021

Classification of diffraction patterns using a convolutional neural network in single particle imaging experiments performed at X-ray free-electron lasers.

[BibT_eX]

[DOI]

CoRR, 2021

How can we learn (more) from challenges? A statistical approach to driving future algorithm development.

[BibT_eX]

[DOI]

CoRR, 2021

The Medical Segmentation Decathlon.

[BibT_eX]

[DOI]

Patrick Ferdinand Christ

Jennifer Goli-Pernicka

CoRR, 2021

GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data.

[BibT_eX]

[DOI]

CoRR, 2021

Common Limitations of Image Processing Metrics: A Picture Story.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Analyzing magnetic resonance imaging data from glioma patients using deep learning.

[BibT_eX]

[DOI]

Comput. Medical Imaging Graph., 2021

GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Automatic image-based pedicle screw planning.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging 2021: Image-Guided Procedures, 2021

Continuous-Time Deep Glioma Growth Models.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

nnDetection: A Self-configuring Method for Medical Object Detection.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Abstract: Studying Robustness of Semantic Segmentation under Domain Shift in Cardiac MRI.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020

From Manual to Automated Design of Biomedical Semantic Segmentation Methods

[BibT_eX]

[DOI]

PhD thesis, 2020

OR-UNet: an Optimized Robust Residual U-Net for Instrument Segmentation in Endoscopic Images.

[BibT_eX]

[DOI]

CoRR, 2020

Robust Medical Instrument Segmentation Challenge 2019.

[BibT_eX]

[DOI]

CoRR, 2020

Studying Robustness of Semantic Segmentation Under Domain Shift in Cardiac MRI.

[BibT_eX]

[DOI]

Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020

nnU-Net for Brain Tumor Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

Abstract: Unsupervised Anomaly Localization Using Variational Auto-Encoders.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Abstract: Deep Probabilistic Modeling of Glioma Growth.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019

The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge.

[BibT_eX]

[DOI]

CoRR, 2019

ModelHub.AI: Dissemination Platform for Deep Learning Models.

[BibT_eX]

[DOI]

CoRR, 2019

An attempt at beating the 3D U-Net.

[BibT_eX]

[DOI]

CoRR, 2019

nnU-Net: Breaking the Spell on Successful Medical Image Segmentation.

[BibT_eX]

[DOI]

CoRR, 2019

Automated brain extraction of multi-sequence MRI using artificial neural networks.

[BibT_eX]

[DOI]

Heinz-Peter Schlemmer

Sabine Heiland

Klaus Hermann Maier-Hein

CoRR, 2019

Computer-assisted intra-operative verification of surgical outcome for the treatment of syndesmotic injuries through contralateral side comparison.

[BibT_eX]

[DOI]

Int. J. Comput. Assist. Radiol. Surg., 2019

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection.

[BibT_eX]

[DOI]

Paul F. Jaeger

Simon A. A. Kohl

Sebastian Bickelhaupt

Tristan Anselm Kuder

Heinz-Peter Schlemmer

Proceedings of the Machine Learning for Health Workshop, 2019

Unsupervised Anomaly Localization Using Variational Auto-Encoders.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Deep Probabilistic Modeling of Glioma Growth.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Efficient Web-Based Review for Automatic Segmentation of Volumetric DICOM Images.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2018

Clickstream Analysis for Crowd-Based Object Segmentation with Confidence.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection.

[BibT_eX]

[DOI]

CoRR, 2018

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

[BibT_eX]

[DOI]

CoRR, 2018

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

[BibT_eX]

[DOI]

Int. J. Comput. Assist. Radiol. Surg., 2018

No New-Net.

[BibT_eX]

[DOI]

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

Abstract: Rekonstruktion der initialen Druckverteilung photoakustischer Bilder mit limitiertem Blickwinkel durch maschinelle Lernverfahren.

[BibT_eX]

[DOI]

Dominik Waibel

Janek Gröhl

Klaus Hermann Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

Advanced Deep Learning Methods.

[BibT_eX]

[DOI]

Klaus Hermann Maier-Hein

Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

[BibT_eX]

[DOI]

CoRR, 2017

Direct White Matter Bundle Segmentation using Stacked U-Nets.

[BibT_eX]

[DOI]

CoRR, 2017

Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge.

[BibT_eX]

[DOI]

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features.

[BibT_eX]

[DOI]

Proceedings of the Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, 2017

Brain Tumor Segmentation Using Large Receptive Field Deep Convolutional Neural Networks.

[BibT_eX]

[DOI]

David Bonekamp

Heinz-Peter Schlemmer