Introduction and Keynote
00:00:00 Welcome address (Katharina Breininger)
00:01:45 Introduction (Katharina Breininger, Christof Bertram)
00:36:09 Reference approaches (Frauke Wilm)
00:49:53 Keynote: An industrial perspective on digital pathology & mitosis detection (Rutger Fick)
Oral Session 1
01:43:04 Yang Chen: Multi Task RetinaNet for Mitosis Detection
01:52:12 Satoshi Kondo: Tackling Mitosis Domain Generalization in Histopathology Images with Color Normalization
01:56:22 Engin Bozaba: Mitosis Detection using YOLOv5 and EfficientNet
02:01:44 Hongyan Gu: Detecting Mitoses with a Convolutional Neural Network
02:08:49 Sen Yang: SK-Unet Model with Fourier Domain and Weight Perturbation for Mitosis Detection
02:13:29 Q&A Session 1
Oral Session 2
02:22:53 Jonas Annuscheit: Radial Prediction Domain Adaption Classifier
02:32:40 Mostafa Jahanifar: Stain-Robust Mitotic Figure Detection
02:39:04 Maxime Lafarge: Semi-Supervised Hard-Negative Mining and Color Augmentation Strategies
02:43:53 Sujatha Kotte: A Deep Learning-based Ensemble Model for Generalized Mitosis detection in H&E stained Whole Slide Images & Attention-based Transformers for Mitosis Domain Generalization in H&E stained WSIs
02:58:10 Q&A Session 2
Results and Awards
03:08:00 Marc Aubreville: Results & Awards
03:39:21 Feedback and Q&A
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