Patent Application for Pathology Image Analysis Method

ChangeBridge: Patent Apps - Health Informatics (G16H)

Detected March 26th, 2026

Summary

The USPTO has published a patent application (US20260088157A1) detailing a method for analyzing pathology image data. The invention focuses on identifying sets of image elements representative of sample properties using confidence scores and thresholds for pathology analysis.

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What changed

This document is a published patent application from the USPTO, not a regulatory rule or guidance. It describes a novel method for pathology image analysis, involving receiving image data, applying functions to determine confidence scores for image elements, comparing these scores against thresholds to identify candidate sets of elements, and associating these sets with a sample property identifier if a confirmation threshold is met.

While not a direct regulatory mandate, this patent application signals potential technological advancements in digital pathology and AI-driven diagnostics. Companies involved in developing or utilizing AI for medical image analysis, particularly in pathology, should be aware of emerging intellectual property in this space. There are no immediate compliance actions required, but it may influence future product development and R&D strategies in the healthcare technology sector.

Source document (simplified)

← USPTO Patent Applications

Identifying Sets of Image Elements as Representative of a Sample Property for Pathology

Application US20260088157A1 Kind: A1 Mar 26, 2026

Inventors

Juha REUNANEN, Kaisa HELMINEN

Abstract

A method of identifying sets of image elements as representative of a sample property for pathology includes receiving pathology image data representing sample images representing adjacent or overlapping portions of a sample for analysis in pathology, each of the sample images including sample image elements; causing a function to be applied to the sample images to determine confidence scores associated with the sample image elements and representing a level of confidence that the associated sample image element represents the sample property; comparing the confidence scores with a candidate confidence threshold to identify a candidate set of adjacent sample image elements, each associated with a confidence score greater than the candidate confidence threshold; determining whether a representative confidence score is greater than a confirmation confidence threshold; and, if so, associating the candidate set of adjacent sample image elements with a sample property identifier.