Apparatuses and a method for artifact reduction in medical images using a neural network
US11026642B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2019 |
| Grant date | Jun 8, 2021 |
| Priority date | — |
| Expiry date | Jun 7, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/50
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and apparatuses are provided that use a neural network to correct artifacts in computed tomography (CT) images, especially cone-beam CT (CBCT) artifacts. The neural network is trained using a training dataset of artifact-minimized images paired with respective artifact-exhibiting images. In some embodiments, the artifact-minimized images are acquired using a small cone angle for the X-ray beam, and the artifact-exhibiting images are acquired either by forwarding projecting the artifact-minimized images using a large-cone-angle CBCT configuration or by performing a CBCT scan. In some embodiments, the network is a 2D convolutional neural network, and an artifact-exhibiting image is applied to the neural network as 2D slices taken for the coronal and/or sagittal views. Then the 2D image results from the neural network are reassembled as a 3D imaging having reduced imaging artifacts.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.