Deep learning based scatter correction
US11769277B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 28, 2018 |
| Grant date | Sep 26, 2023 |
| Priority date | — |
| Expiry date | Sep 9, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2211/441
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An imaging system includes a computed tomography (CT) imaging device (10) (optionally a spectral CT), an electronic processor (16, 50), and a non-transitory storage medium (18, 52) storing a neural network (40) trained on simulated imaging data (74) generated by Monte Carlo simulation (60) including simulation of at least one scattering mechanism (66) to convert CT imaging data to a scatter estimate in projection space or to convert an uncorrected reconstructed CT image to a scatter estimate in image space. The storage medium further stores instructions readable and executable by the electronic processor to reconstruct CT imaging data (12, 14) acquired by the CT imaging device to generate a scatter-corrected reconstructed CT image (42). This includes generating a scatter estimate (92, 112, 132, 162, 182) by applying the neural network to the acquired CT imaging data or to an uncorrected CT image (178) reconstructed from the acquired CT imaging data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.