Using high-resolution micro-computed tomography (µCT) and artificial intelligence, a group led by physicist Goran Lovric from the PSI Center for Photon Science generated virtual stains of tissue samples, so-called histological stains.
This could potentially eliminate the need to prepare and stain ultrathin, delicate sections.
To achieve this, the researchers trained a specialized AI model using pairs of real histological sections and their corresponding CT scans.
In this way, the AI model learned which microscopic patterns typically receive which staining.
It then was able to virtually stain new CT data—essentially an automatic translation between two image worlds.
The researchers tested their new method on lung tissue taken from individuals with pulmonary hypertension.
The new technique can be automated and can work significantly faster than the current method.
However, it is not yet ready for routine use in hospitals.
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