UCLA Researchers Propose A Deep Learning-Based AI Framework To Re-Stain Images Of Tissue Biopsy

Pathologists examine histochemically stained tissue biopsy sections to make medical diagnoses. Hematoxylin and eosin (H&E) is the most widely used histochemical stain in pathology, accounting for the vast majority of human tissue biopsy stains worldwide. In many clinical cases, however, additional "special stains" are required to bring contrast and color to various tissue components and allow pathologists to obtain a clearer diagnostic image. These specific stains frequently necessitate much more tissue preparation time, as well as tedious effort and monitoring by specialist histotechnologists, all of which raise the expenses and length of time to diagnose. By computationally translating existing photos of H&E stained tissue into special stains, UCLA researchers devised a deep learning-based approach that can be used to eliminate the need for these specific stains to be prepared by human histotechnologists.