Systems and methods to process electronic images to categorize intra-slide specimen tissue type
US11544849B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 30, 2021 |
| Grant date | Jan 3, 2023 |
| Priority date | — |
| Expiry date | Dec 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed for identifying tissue specimen types present in digital whole slide images. In some aspects, tissue specimen types may be identified using unsupervised machine learning techniques for out-of-distribution detection. For example, a digital whole slide image of a tissue specimen and a recorded tissue specimen type for the digital whole slide image may be received. One or more feature vectors may be extracted from one or more foreground tiles of the digital whole slide image identified as including the tissue specimen, and a distribution learned by a machine learning system for the recorded tissue specimen type may be received. Using the distribution, a probability of the feature vectors corresponding to the recorded tissue specimen type may be computed and used as a basis for classifying the foreground tiles from which the feature vectors are extracted as an in-distribution foreground tile or an out-of-distribution foreground tile.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.