Diffusion-based Virtual Staining from Polarimetric Mueller Matrix Imaging

• URL: http://arxiv.org/abs/2503.01352v1
• Date: Mon, 03 Mar 2025 09:45:27 GMT
• Title: Diffusion-based Virtual Staining from Polarimetric Mueller Matrix Imaging
• Authors: Xiaoyu Zheng, Jing Wen, Jiaxin Zhuang, Yao Du, Jing Cong, Limei Guo, Chao He, Lin Luo, Hao Chen,
• Abstract summary: We propose a Regulated Bridge Diffusion Model (RBDM) for polarization-based virtual staining.<n>RBDM learns the mapping from polarization images to other modalities such as H&E and fluorescence.<n>Experiment results show that our model greatly outperforms other benchmark methods.
• Score: 8.016374085889172
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Polarization, as a new optical imaging tool, has been explored to assist in the diagnosis of pathology. Moreover, converting the polarimetric Mueller Matrix (MM) to standardized stained images becomes a promising approach to help pathologists interpret the results. However, existing methods for polarization-based virtual staining are still in the early stage, and the diffusion-based model, which has shown great potential in enhancing the fidelity of the generated images, has not been studied yet. In this paper, a Regulated Bridge Diffusion Model (RBDM) for polarization-based virtual staining is proposed. RBDM utilizes the bidirectional bridge diffusion process to learn the mapping from polarization images to other modalities such as H\&E and fluorescence. And to demonstrate the effectiveness of our model, we conduct the experiment on our manually collected dataset, which consists of 18,000 paired polarization, fluorescence and H\&E images, due to the unavailability of the public dataset. The experiment results show that our model greatly outperforms other benchmark methods. Our dataset and code will be released upon acceptance.

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