Predicting overall survival in early stage lung cancer with feature driven local cell graphs (FEDEG)
US11455718B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 1, 2019 |
| Grant date | Sep 27, 2022 |
| Priority date | — |
| Expiry date | Jun 24, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments include accessing an image of a region of tissue demonstrating cancerous pathology; detecting a plurality of cells represented in the image; segmenting a cellular nucleus of a first member of the plurality of cells and a cellular nucleus of at least one second, different member of the plurality of cells; extracting a set of nuclear morphology features from the plurality of cells; constructing a feature driven local cell graph (FeDeG) based on the set of nuclear morphology features and a spatial relationship between the cellular nuclei using a mean-shift clustering approach; computing a set of FeDeG features based on the FeDeG; providing the FeDeG features to a machine learning classifier; receiving, from the machine learning classifier, a classification of the region of tissue as a long-term or a short-term survivor, based, at least in part, on the set of FeDeG features; and displaying the classification.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.