Prediction of myelin stainings using 7T MRI and deep learning

Motivation: Histological examination of the brain provides precise analyses of brain tissue, but requires ex vivo tissue samples. In vivo MRI offers an alternative but still has limitations. Goal(s): Predict histologic images from in vivo MR images. Approach: Utilize deep learning generative models to create brain histological images from multi contrast MR images. Results: The appropriate combination of MRI contrasts can generate myelin histology images. Impact: Generating myelin histological images significantly impacts brain tissue property research by providing ex vivo information. This adaptable technique extends its applicability to various tissue properties, providing broader insights into histology and beyond.