MIDOG 2021 MICCAI Workshop: Preliminary program available

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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