Multivariate Image Analysis of Magnetic Resonance Images with the Direct Exponential Curve Resolution Algorithm (DECRA): Part 2: Application to Human Brain Images

Owing to the heterogeneity of living tissues, it is challenging to quantify tissue properties using magnetic resonance imaging. Within a single voxel, contributions to the signal may result from several types of¹H nuclei with varied chemical (e.g., −CH₂−, −OH) and physical environments (e.g., tissue density, compartmentalization). Therefore, mixtures of¹H environments are prevalent. Furthermore, each unique type of¹H environment may possess a unique and characteristic spin–lattice relaxation time (T₁) and spin–spin relaxation time (T₂). A method for resolving these unique exponentials is introduced in a separate paper (Part 1. Algorithm and Model System) and uses the direct exponential curve resolution algorithm (DECRA). We present results from an analysis of images of the human head comprising brain tissues.