A novel multi-modal label-free imaging system is proposed for histopathology, which provides uniformly reconstructed virtual-stained brightfield images and corresponding QPI images. The system was tested on urinal histopathology, to detect and segment glomerulus. From each modality, over 90% of IoU scores were obtained and accelerated performance was obtained through multi-modal learning. Briefly, histopathology quantification with label-free samples is a feasible method via the proposed novel system.
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