Diffusion-Based Domain Adaptation for Improved Cell Counting

This research explores using diffusion models to address the domain gap problem in cell counting, which often arises when models are trained on one dataset and applied to another. The approach suggests a promising path for enhancing the generalizability and performance of cell counting algorithms across different datasets.

• •Applies diffusion models to domain adaptation in cell counting.
• •Addresses the challenge of domain gaps in medical image analysis.
• •Aims to improve the robustness and generalizability of cell counting algorithms.