University of Michigan

James Balter

Yue Cao

Jeffrey Allen Fessler

Lianli Liu

Yong Long

Adam Johansson

The following relates generally to motion prediction in magnetic resonance (MR) imaging. In some embodiments, a 'modular' approach is taken to motion correction. That is, individual motion sources (e.g., a patient's breathing, heartbeat, stomach contractions, peristalsis, and so forth) are accounted for individually in the motion correction. In some embodiments, to correct for a particular motion source, a reference state is created from a volume of interest (VOI), and other states are created and deformably aligned to the reference state.

Hierarchical motion modeling from dynamic magnetic resonance imaging

A computer-implemented method is provided for generating patient models from multiple imaging contrast sources which may be, for example from magnetic resonance imaging without computed tomography. The method includes: acquiring multiple sets of image data representing a volume of a patient using magnetic resonance imaging, wherein each set of image data is acquired in a different manner so as to create contrast amongst tissue types of the patient; classifying tissue in each voxel in the volume using the multiple sets of image data as input to a classification algorithm; and generating a patient model for the volume from probability distributions of the classes of tissue as derived from the classification algorithm.

Patient modeling from multispectral input image volumes

Methods provided for forward and back-projection, which are referred to as separable footprint (SF) projectors: exemplified by the SF-TR and SF-TT projectors. These methods approximate the voxel footprint functions as 2D separable functions. Because of the separability of these footprint functions, calculating their integrals over a detector cell is greatly simplified and can be implemented efficiently. In some embodiments, the SF-TR projector uses trapezoid functions in the transaxial direction and rectangular functions in the axial direction. In some embodiments, the SF-TT projector uses trapezoid functions in both the axial and transaxial directions. Simulations and experiments showed that both SF projector methods are more accurate than conventional distance-driven (DD) projectors. Moreover, the SF-TT projector is more accurate than the SF-TR projector for rays associated with large cone angles. In some embodiments, the SF-TR projector has similar computation speed with the DD projector and the SF-TT projector is about two times slower.

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Ann Arbor, MI, United States of America

James Balter