One-Step Image Reconstruction for Cine MRI with a Quadratic Constraint

In cine MRI, the measurements within each timeframe alone are too noisy for image reconstruction. Some information must be 'borrowed' from other time frames and the reconstruction algorithm is a slow iterative procedure.

We set up a constrained objective function, which uses the measurements at other time frames to regularize the image reconstruction. We derive a non-iterative algorithm to minimize this objective function.

The derivation of the algorithm is based on the calculus of variations. The resultant algorithm is in the form of filtered backprojection.

The feasibility of the proposed algorithm is demonstrated with a clinical patient brain study.

Non-iterative reconstruction that minimizes a constrained objective function significantly increases the throughput in healthcare institutions. This may translate to reduced healthcare costs. The new reconstruction formula has a closed form that gives an explicit expression of how to incorporate the reference image in dynamic reconstruction.