Method of quantifying magnetic resonance diffusion parameters by using diffusion weighted magnetic resonance images
US12310713B2 · kind B2 · utility
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Key dates
| Filing date | Jan 31, 2023 |
| Grant date | May 27, 2025 |
| Priority date | — |
| Expiry date | Jul 6, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10088
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Disclosed is an unsupervised deep learning method, which simultaneously performs registration between diffusion weighted magnetic resonance images and quantification of diffusion parameters. The unsupervised deep learning method decreases a registration error caused by a contrast difference by comparing a similarity between images of the same contrast, increases the performance of registration, and increases the accuracy of quantifying magnetic resonance diffusion parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.