Deep learning medical systems and methods for image reconstruction and quality evaluation
US10565477B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 15, 2019 |
| Grant date | Feb 18, 2020 |
| Priority date | — |
| Expiry date | Jul 15, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30168
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and apparatus to automatically generate an image quality metric for an image are provided. An example method includes automatically processing a first medical image using a deployed learning network model to generate an image quality metric for the first medical image, the deployed learning network model generated from a digital learning and improvement factory including a training network, wherein the training network is tuned using a set of labeled reference medical images of a plurality of image types, and wherein a label associated with each of the labeled reference medical images indicates a central tendency metric associated with image quality of the image. The example method includes computing the image quality metric associated with the first medical image using the deployed learning network model by leveraging labels and associated central tendency metrics to determine the associated image quality metric for the first medical image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.