Systems and methods for detecting cardiovascular anomalies using spatiotemporal neural networks
US12148162B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 12, 2024 |
| Grant date | Nov 19, 2024 |
| Priority date | — |
| Expiry date | Jan 12, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30101
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Systems and methods are provided for processing image data generated by a medical imaging device such as an ultrasound or echocardiogram device and processing the image data using artificial intelligence and machine learning to determine a presence of one or more congenital heart defects (CHDs) and/or other cardiovascular anomalies in the image data and/or to determine key-point and/or contour detection. The image processing system may be used to detect CHDs and/or other cardiovascular anomalies in a fetus. The image data may be processed using a spatiotemporal convolutional neural network (CNN). The spatiotemporal CNN may include a spatial CNN for image recognition and a temporal CNN for processing optical flow data based on the image data. The outputs of the spatial CNN and the temporal CNN may be fused (e.g., using late fusion) to generate a likelihood of CHDs and/or other cardiovascular anomalies.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.