Deep learning based three-dimensional reconstruction method for low-dose PET imaging
US12118649B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Jan 23, 2021 |
| Grant date | Oct 15, 2024 |
| Priority date | — |
| Expiry date | Jul 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2211/441
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed is a three-dimensional low-dose PET reconstruction method based on deep learning. The method comprises the following steps: back projecting low-dose PET raw data to the image domain to maintain enough information from the raw data; selecting an appropriate three-dimensional deep neural network structure to fit the mapping between the back projection of the low-dose PET and a standard-dose PET image; after learning from the training samples the network parameters are fixed, realizing three-dimensional PET image reconstruction starting from low-dose PET raw data, thereby obtaining a low-dose PET reconstructed image which has a lower noise and a higher resolution compared with the traditional reconstruction algorithm and image domain noise reduction processing.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.