A Model for Resolving Flow Parameters for MRI-Neuroimaging Application

Abstract

The functionality of recent neuroimaging using the MRI machine has generated errors which are peculiar to all kinds of MRI processes. Though hardwares are used to complement the MRI process, the problems are not completely solved due to its fundamental errors. The fundamental error is in the exclusion of molecular interaction in the ab-initio Bloch NMR. A new mathematical concept was applied to resolve the functionality problems. The Bloch NMR features and the molecular interactions were fused via a Hamiltonian process. The simulation obtained reveals the tendencies of signals to diverge. This concept was summarized via a concept known as the signal loss factor 'E'. The signal loss factor 'E' exists when spin velocity fluctuates due to compartmental boundaries in the macromolecular sites. We propose that the fundamental error-signal loss factor 'E', is a vital factor required for clinical diagnosis of cognitive impairment.