Graph-based prostate diagnosis network and method for using the same
US11963788B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2021 |
| Grant date | Apr 23, 2024 |
| Priority date | — |
| Expiry date | Dec 22, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
The present invention provides a graph-based prostate diagnosis network (GPD-Net) and a method for using the same to predict a prostate health status of a patient from a 3D magnetic resonance imaging (MRI) scan containing a plurality of 2D MRI slices. The GPD-Net only demands patient-level annotations of MRI scan for training by formulating the diagnosis task of 3D prostate MRI scan in a multi-instance learning (MIL) strategy, and regarding each 2D MRI slice in the 3D prostate MRI scan as an instance. The GPD-Net includes a plurality of importance-guided graph convolutional layers to explore the diagnostic information with the importance-based topology. The present invention provides accurate prediction of prostate diseases and achieve more reliable diagnosis from MRI scans, therefore can effectively alleviate the workload of clinician in viewing the slices of MRI scan.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.