System for reconstruction of virtual frequency selective inversion MR images

摘要

A virtual frequency selective inversion (VFSI) method receives at least one MR image representative dataset and an associated phase reference dataset, and classifies anatomical material into a first component representing anatomical material having a first range of resonance frequencies associated with a first range of phase differences between the MR image representative dataset and the associated phase reference image dataset, and a second component representing anatomical material having a second range of resonance frequencies associated with a second range of phase differences between the MR image representative dataset and the associated phase reference image dataset. The method assigns different visual attributes to first and second components derived using phase differences between the MR image representative dataset and the reference image dataset and displays an image.

主权项

1. A method for processing MRI data employing virtual frequency selective inversion, comprising the steps of:
receiving at least one MR image representative dataset and an associated phase reference dataset; deriving from the at least one MR image representative dataset and the associated phase reference dataset,
a first component representing anatomical material having a first range of resonance frequencies associated with a first range of phase differences between the MR image representative dataset and the associated phase reference dataset and,a second component representing anatomical material having a second range of resonance frequencies associated with a second range of phase differences between the MR image representative dataset and the associated phase reference dataset; assigning different visual attributes to the derived first and second components; and displaying an image comprising at least one of (a), the derived first component (b) the derived second component, (c) a composite of the derived first and second components, and (d) a composite of the MR image representative dataset and at least one of the first and second derived components.