Estimating object thickness with neural networks
US11514573B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 8, 2020 |
| Grant date | Nov 29, 2022 |
| Priority date | — |
| Expiry date | Feb 11, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein are neural network-based systems, methods and instrumentalities associated with estimating a thickness of an anatomical structure based on a visual representation of the anatomical structure and a machine-learned thickness prediction model. The visual representation may include an image or a segmentation mask of the anatomical structure. The thickness prediction model may be learned based on ground truth information derived by applying a partial differential equation such as Laplace's equation to the visual representation and solving the partial differential equation. When the visual representation includes an image of the anatomical structure, the systems, methods and instrumentalities described herein may also be capable of generating a segmentation mask of the anatomical structure based on the image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.