Machine learning for digital pathology
US12085568B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 7, 2023 |
| Grant date | Sep 10, 2024 |
| Priority date | — |
| Expiry date | Nov 7, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method assessing tissue morphology using machine learning includes a step of training a machine learnable device to predict the status of a diagnostic feature in stained tissue samples. The machine learnable device is trained with a characterized set of digital images of stained tissue samples. Each digital image of the characterized set has a known status for the diagnostic feature and an extracted feature map provides values for a extracted feature over an associated 2-dimensional grid of spatial locations. A step of inputting the set of extracted feature maps is inputted into the machine learnable device to form associations therein between the set of extracted feature maps to and the known status for the diagnostic feature to form a trained machine learnable device. The status for the diagnostic feature of a stained tissue sample of unknown status for the diagnostic feature is predicted from the trained machine learnable device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.