Image-based tumor phenotyping with machine learning from synthetic data
US10282588B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 2, 2017 |
| Grant date | May 7, 2019 |
| Priority date | — |
| Expiry date | May 2, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2218/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Machine training and application of machine-trained classifier are used for image-based tumor phenotyping in a medical system. To create a training database with known phenotype information, synthetic medical images are created. A computational tumor model creates various examples of tumors in tissue. Using the computational tumor model allows one to create examples not available from actual patients, increasing the number and variance of examples used for machine-learning to predict tumor phenotype. A model of an imaging system generates synthetic images from the examples. The machine-trained classifier is applied to images from actual patients to predict tumor phenotype for that patient based on the knowledge learned from the synthetic images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.