Dictionary learning based image reconstruction
US9824468B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 31, 2015 |
| Grant date | Nov 21, 2017 |
| Priority date | — |
| Expiry date | May 27, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/031
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computationally efficient dictionary learning-based term is employed in an iterative reconstruction framework to keep more spatial information than two-dimensional dictionary learning and require less computational cost than three-dimensional dictionary learning. In one such implementation, a non-local regularization algorithm is employed in an MBIR context (such as in a low dose CT image reconstruction context) based on dictionary learning in which dictionaries from different directions (e.g., x,y-plane, y,z-plane, x,z-plane) are employed and the sparse coefficients calculated accordingly. In this manner, spatial information from all three directions is retained and computational cost is constrained.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.