Integrating macrostructural and microstructural representations of white matter through convolutional neural networks
Jung Youn Min, Heehwan Wang, Jiook Cha · FENS Forum 2024
White matter is pivotal for efficient brain communication. Fractional Anisotropy (FA) from diffusion tensor imaging has been widely used to estimate the microstructural integrity of white matter. However, the extensive fibrous structure of the white matter, varying widely across individuals, necessitates an analytic approach capable of capturing both its macroscopic and microscopic structures effectively. We hypothesized that a deep neural network approach could learn multi-scale features of white matter in an end-to-end manner. We analyzed data from the Adolescent Brain Cognitive Development
ePoster · Neuroscience