In a new study from Boston University Chobanian & Avedisian School of Medicine and BU’s College of Engineering, researchers used a special microscope called birefringence microscopy (BRM) paired with an automated deep learning algorithm to reliably count and map myelin damage across whole sections of the brain—something not feasible with other techniques. The ability to image and measure damage to myelin will lead to better understanding of the patterns and extent that occurs with disease, injury and normal aging.

The study is published in the journal Neurophotonics.

“A major advantage of BRM over conventional imaging methods is its ability to rapidly image large areas at high resolution without special staining, making it uniquely suited for studying widespread myelin pathology,” says corresponding author Alex Gray, Ph.D., ’25.