Distributed Computation of Linear Inverse Problems with Application to Computed Tomography

Understand

The inversion of linear systems is a fundamental step in many inverse problems.

• Computational challenges exist when trying to invert large linear systems, where limited computing resources mean that only part of the system can be kept in computer memory at any one time.
• We are here motivated by tomographic inversion problems that often lead to linear inverse problems.
• In state of the art x-ray systems, even a standard scan can produce 4 million individual measurements and the reconstruction of x-ray attenuation profiles typically requires the estimation of a million attenuation coefficients.