Adaptive image filtering for volume reconstruction using partial image data
US10967202B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 4, 2019 |
| Grant date | Apr 6, 2021 |
| Priority date | — |
| Expiry date | Sep 23, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20081
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
A method of generating an image synthesis process is disclosed, where the image synthesis process improves image quality of degraded volumetric images. In the method, a machine learning process is trained in a supervised learning framework as the image synthesis process. In the supervised learning process, a lower-quality partial-data reconstruction of a target volume is employed as an input object in the supervised learning process and a higher-quality full data reconstruction of the target volume is employed as an expected output. The full data reconstruction is generated based on a first set of projection images of the three-dimensional volume and the partial-data reconstruction is generated based on a second set of projection images of the three-dimensional volume, where the second set of projection images includes projection images that have less image information and/or are of a lower image quality than the first set of projection images.
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