Similarity based per item model selection for medical imaging
US11288797B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 8, 2020 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Jul 22, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments may include techniques to choose a model based on a similarity of computed features of an input to computed features of several models in order to improve feature analysis using Machine Learning models. A method of image analysis may comprise extracting a training feature vector corresponding to each of the plurality of machine learning models from each validation image from a plurality of machine learning models trained using a plurality of validation images, extracting from a new image a new feature vector corresponding to each of the plurality of machine learning models, comparing each new feature vector corresponding to each machine learning model with the training feature vector corresponding to each of the plurality of machine learning models, and selecting and outputting an inference for the new image generated by the machine learning model for which the new feature vector and the training feature vector are most similar.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.