A First-Order Framework for Inverse Imaging Problems

We argue that some inverse problems arising in imaging can be efficiently treated using only single-precision (or other reduced-precision) arithmetic, using a combination of old ideas (first-order methods, polynomial preconditioners), and new ones (bilateral filtering, total variation). Using single precision, and having structures which parallelize in the ways needed to take advantage of low-cost/high-performance multi-core/SIMD … Read more

Magnetic Resonance Tissue Density Estimation using Optimal SSFP Pulse-Sequence Design

In this paper, we formulate a nonlinear, nonconvex semidefinite optimization problem to select the steady-state free precession (SSFP) pulse-sequence design variables which maximize the contrast to noise ratio in tissue segmentation. The method could be applied to other pulse sequence types, arbitrary numbers of tissues, and numbers of images. To solve the problem we use … Read more