Automatic generation of fundus drawings
AssigneeMicrosoft Technology Licensing, LLC
InventorsPrashant Gupta, Manish Gupta, Mithun Das Gupta
Life of this patent
Estimating the term…
Abstract
Techniques for automating the generation and analysis of fundus drawings are described. Captured images undergo image processing to extract information about image features. Fundus images are generated and recommended labels for the fundus drawing are generated. Fundus drawings can be analyzed and undergo textual processing to extract existing labels. Machine learning models and co-occurrence analysis can be applied to collections of fundus images and drawings to gather information about commonly associated labels, label locations, and user information. The most frequently used labels associated with the image can be identified to improve recommendations and personalize labels.
Claims21
1-20. (canceled)
A method implemented by one or more computing devices, comprising:
- receiving data indicative of a first medical image;
- identifying one or more image features, the one or more image features being indicative of a condition or a label associated with the first medical image;
- generating a second medical image based on the one or more image features;
- associating a classifier with the one or more image features;
- and
- applying one or more recommendation models to identify, based at least in part on the associated classifier, one or more recommended labels and a label location within the second medical image for each of the one or more recommended labels.
A system, comprising:
- one or more processors;
- and
- a memory storing computer readable instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
- identifying one or more image features indicative of condition or a label associated with a medical image;
- identifying a classifier to be associated with the one or more image features;
- and
- applying one or more recommendation models to identify, based at least in part on the associated classifier, one or more recommended labels and a label location within the medical image for each of the one or more recommended labels.
A method implemented by one or more computing devices, comprising:
- identifying one or more image features indicative of a condition or a label associated with a medical image;
- associating a classifier with the one or more image features;
- identifying one or more recommended labels;
- and
- applying one or more recommendation models to identify, based at least in part on the associated classifier, a label location within the medical image for each of the one or more recommended labels.
Dependencies are inferred from the claim text.