Systems and methods for feature detection in retinal images
US10115194B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 6, 2016 |
| Grant date | Oct 30, 2018 |
| Priority date | — |
| Expiry date | Sep 16, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30041
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Provided is a method for training a neural network to detect features in a retinal image. The method may include the steps of: combining and randomizing feature images into a Training data set; combining and randomizing the feature images into a testing dataset; training a plurality of neural networks having different architectures using a subset of the training dataset while testing on a subset of the testing dataset; identifying the best neural network based on each of the plurality of neural networks performance on the testing data set; inputting images to the best neural network and identifying a limited number of false positives and false negative and adding the false positives and false negatives to the training dataset and testing dataset; and repeating the foregoing steps until an objective performance threshold is reached.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.