Video: MIDOG 2022 workshop

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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