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davidanglada / DualU-NetView on GitHub
DualU-Net is a multi-task deep learning model for nuclei segmentation and classification. It employs a dual-decoder design that predicts both pixel-wise segmentation maps and Gaussian-based centroid density maps, enabling fast and accurate instance segmentation in histopathological images.
☆11Jun 2, 2025Updated last year

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