We are presenting a first and still preliminary schedule of the MIDOG challenge workshop. Congratulation to all accepted presenters! Please Note that all times are UTC! Links to the
Block 1: Introduction and Reference Approach, 14:00-15:20 UTC (16:00 – 17:20 CEST)
| 14:00-14:20 | Welcome address and Introduction | Marc Aubreville |
| 14:20-15:05 | Keynote: How to build trustworthy AI solutions | Tobias Heimann |
| 15:05-15:20 | Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmain Generalization (MIDOG) Challenge | Frauke Wilm |
Block 2: Oral Session 1: Cascaded and Multi-stage approaches for mitosis detection
15:30-16:05 UTC (17:30 – 18:05 CEST)
| 15:30-15:35 | Cascade RCNN for MIDOG Challenge | Salar Razavi |
| 15:35-15:40 | Domain Adaptive Cascade R-CNN for Mitosis DOmain Generalization (MIDOG) Challenge | Ying Cheng |
| 15:40-15:45 | Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classification Model for MIDOG Challenge | Yubo Wang |
| 15:45-15:50 | Two-step Domain Adaptation for Mitosis Cell Detection in Histopathology Images | Ramin Nateghi |
| 15:50-16:05 | Q&A and Discussion | all |
Block 3: Oral Session 2: Instance segmentation-based and adversarial approaches
16:05-16:40 UTC (18:05 – 18:40 CEST)
| 16:05-16:10 | Multi-source Domain Adaptation Using Gradient Reversal Layer for Mitotic Cell Detection | Satoshi Kondo |
| 16:10-16:15 | Sk-Unet Model with Fourier Domain for Mitosis Detection | Sen Yang |
| 16:15-16:20 | Robust Mitosis Detection Using a Cascade Mask-RCNN Approach With Domain-Specific Residual Cycle-GAN Data Augmentation | Rutger Fick |
| 16:20-16:25 | Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge | Mostafa Jahanifar |
| 16:25-16:40 | Q&A and Discussion | all |
Block 4: Oral Session 3: Augmentation strategies for domain invariance
16:40-17:15 UTC (18:40 – 19:15 CEST)
| 16:40-16:45 | Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge | Maxime Lafarge |
| 16:45-16:50 | Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images | Jack Breen |
| 16:50-16:55 | Domain-Robust Mitotic Figure Detection with StyleGAN | Youjin Chung |
| 16:55-17:00 | MitoDet: Simple and robust mitosis detection | Jakob Dexl |
| 17:00-17:15 | Q&A and Discussion | all |
Block 5: Results and Awards, Panel Discussion
17:25-18:00 UTC (19:25-20:00 CEST)
| 17:25-17:40 | Results and Awards | Marc Aubreville, Katharina Breininger |
| 17:40-18:00 | Panel Discussion | The MIDOG Organizers |
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