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Preface MIDOG 2021
Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmainGeneralization Challenge
Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images
Domain-Robust Mitotic Figure Detection with StyleGAN
Two-step Domain Adaptation for Mitosis Cell Detection in Histopathology Images
Robust Mitosis Detection Using a Cascade Mask-RCNN Approach With Domain-Specific Residual Cycle-GAN Data Augmentation
Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge
MitoDet: Simple and robust mitosis detection
Multi-source Domain Adaptation Using Gradient Reversal Layer for Mitotic Cell Detection
Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge
Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classi cation Model for MIDOG Challenge
Domain Adaptive Cascade R-CNN for Mitosis DOmain Generalization (MIDOG) Challenge
Reducing Domain Shift For Mitosis Detection Using Preprocessing Homogenizers
Cascade RCNN for MIDOG Challenge
Sk-Unet Model with Fourier Domain for Mitosis Detection
Preface MOOD21
Self-Supervised 3D Out-of-Distribution Detection via Pseudoanomaly Generation
Self-Supervised Medical Out-of-Distribution Using U-Net Vision Transformers
SS3D: Unsupervised Out-of-Distribution Detection and Localization for Medical Volumes
MetaDetector: Detecting Outliers by Learning to Learn from Self-supervision
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation
Preface Learn2Reg 2021
Deformable Registration of Brain MR Images via a Hybrid Loss
Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge
Unsupervised Volumetric Displacement Fields Using Cost Function Unrolling
Conditional Deep Laplacian Pyramid Image Registration Network in Learn2Reg Challenge
The Learn2Reg 2021 MICCAI Grand Challenge (PIMed Team)
Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021
Progressive and Coarse-to-fine Network for Medical Image Registration across Phases, Modalities and Patients. -Semi-supervised Multilevel Symmetric Image Registration Method for Magnetic Resonance Whole Brain Images. .
Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmainGeneralization Challenge
Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images
Domain-Robust Mitotic Figure Detection with StyleGAN
Two-step Domain Adaptation for Mitosis Cell Detection in Histopathology Images
Robust Mitosis Detection Using a Cascade Mask-RCNN Approach With Domain-Specific Residual Cycle-GAN Data Augmentation
Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge
MitoDet: Simple and robust mitosis detection
Multi-source Domain Adaptation Using Gradient Reversal Layer for Mitotic Cell Detection
Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge
Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classi cation Model for MIDOG Challenge
Domain Adaptive Cascade R-CNN for Mitosis DOmain Generalization (MIDOG) Challenge
Reducing Domain Shift For Mitosis Detection Using Preprocessing Homogenizers
Cascade RCNN for MIDOG Challenge
Sk-Unet Model with Fourier Domain for Mitosis Detection
Preface MOOD21
Self-Supervised 3D Out-of-Distribution Detection via Pseudoanomaly Generation
Self-Supervised Medical Out-of-Distribution Using U-Net Vision Transformers
SS3D: Unsupervised Out-of-Distribution Detection and Localization for Medical Volumes
MetaDetector: Detecting Outliers by Learning to Learn from Self-supervision
AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation
Preface Learn2Reg 2021
Deformable Registration of Brain MR Images via a Hybrid Loss
Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge
Unsupervised Volumetric Displacement Fields Using Cost Function Unrolling
Conditional Deep Laplacian Pyramid Image Registration Network in Learn2Reg Challenge
The Learn2Reg 2021 MICCAI Grand Challenge (PIMed Team)
Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021
Progressive and Coarse-to-fine Network for Medical Image Registration across Phases, Modalities and Patients. -Semi-supervised Multilevel Symmetric Image Registration Method for Magnetic Resonance Whole Brain Images. .