The Domain Adaptive Cascade R-CNN for Mitosis Domain Generalization (MIDOG) Challenge was conducted by authors Xi Long, Ying Cheng, Xiao Mu, Lian Liu, and Jingxin Liu. They developed a method for mitosis detection in digital histopathology images, achieving an F1 score of 0.7500 on the preliminary test set in the challenge at MICCAI 2021. Their approach involved comprehensive data augmentation and adapting existing popular detection architecture to improve performance. The study highlights the importance of domain adaptation in medical image analysis and demonstrates the effectiveness of their proposed method in addressing this challenge.
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Monodeep Mukherjee reveals new R-CNN insights in Machine Learning 2024 #AI
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