Training a neural network for a predictive aortic aneurysm detection system
US11538163B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 28, 2022 |
| Grant date | Dec 27, 2022 |
| Priority date | — |
| Expiry date | Feb 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/031
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for detecting aortic aneurysms using ensemble based deep learning techniques that utilize numerous computed tomography (CT) scans collected from numerous de-identified patients in a database. The system includes software that automates the analysis of a series of CT scans as input (in DICOM file format) and provides output in two dimensions: (1) ranking CT scans by risks of adverse events from aortic aneurysm, (2) providing aortic aneurysm size estimates. A repository of CT scans may be used for training of deep neural networks and additional data may be drawn from localized patient information from institutions and hospitals which grant permission.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.