USPTO Patent Granted: Medical Image Matching Using Machine Learning

ChangeBridge: Patent Grants - Health Informatics (G16H)

Published March 24th, 2026

Detected March 24th, 2026

Summary

The USPTO has granted a patent to Paige.AI, Inc. for a computer-implemented method using machine learning to process and match electronic medical images. The patent, US12586675B2, was filed on June 2, 2022, and officially granted on March 24, 2026.

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What changed

The United States Patent and Trademark Office (USPTO) has granted patent US12586675B2 to Paige.AI, Inc. This patent covers a computer-implemented method for processing electronic medical images using a trained machine learning system. The system is designed to compare pairs of medical images from a single patient to determine if they match within a predefined similarity threshold, with the output being stored. The patent was filed on June 2, 2022, and officially granted on March 24, 2026.

While this is a patent grant and not a regulatory rule, it signifies a technological advancement in health informatics and AI. Companies involved in medical imaging analysis, AI development for healthcare, or electronic health record systems should be aware of this patented technology. It may influence future product development, licensing agreements, or potential intellectual property considerations within the health informatics sector.

Source document (simplified)

← USPTO Patent Grants

Systems and methods for processing images for image matching

Grant US12586675B2 Kind: B2 Mar 24, 2026

Assignee

Paige.AI, Inc.

Inventors

Christopher Kanan, Leo Grady

Abstract

A computer-implemented method for processing electronic medical images, the method including receiving a plurality of electronic medical images of a medical specimen associated with a single patient. The plurality of electronic medical images may be inputted into to a trained machine learning system, the trained machine learning system being trained to compare each of the plurality of electronic medical images to each other to determine whether each pair of the electronic medical images matches within a predetermined similarity threshold. The trained machine learning system may output whether each pair of the electronic medical images matches within a predetermined similarity threshold. The output may be stored.