Characterizing lung nodule risk with quantitative nodule and perinodular radiomics
US10470734B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 24, 2018 |
| Grant date | Nov 12, 2019 |
| Priority date | — |
| Expiry date | Jul 24, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2211/404
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments associated with classifying a region of tissue using features extracted from nodules and surrounding structures. One example apparatus includes a feature extraction circuit configured to automatically extract a first set of quantitative features from a nodule represented in at least one CT image, and automatically extract a second set of quantitative features from the lung parenchyma region immediately surrounding the nodule represented in the at least one CT image; a feature selection circuit configured to select an optimally predictive feature set from the first set of quantitative features and the second set of quantitative features; and a training circuit configured to train a classifier using the optimally predictive feature set to assign malignancy risk to a lung nodule represented in a CT image of a region of tissue demonstrating lung nodules. A prognosis or treatment plan may be provided based on the malignancy risk.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.