Unsupervised domain adaptive model for 3D prostate zonal segmentation
US12020436B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 6, 2021 |
| Grant date | Jun 25, 2024 |
| Priority date | — |
| Expiry date | Dec 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention provides an unsupervised domain adaptive segmentation network comprises a feature extractor configured for extracting features from a 3D MRI scan image; a decorrelation and whitening module configured for preforming decorrelation and whitening transformation on the extracted features to obtain whitened features; a domain-specific feature translation module configured for translating domain-specific features from a source domain into a target domain for adapting the unsupervised domain adaptive network to the target domain; and a classifier configured for projecting the whitened features into a zonal segmentation prediction. By implementing the domain-specific feature translation module for transferring the knowledge learned from the labeled source domain data to unlabeled target domain data, domain gap between the source and target data can be narrowed. Therefore, the unsupervised domain adaptive segmentation network trained with labeled open-source prostate zonal segmentation dataset (source data) can perform in the target domain without performance degradation.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.