Patent · US Active

Data augmentation for a machine learning method

US12374084B2 · kind B2 · utility

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12Claims

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Assignee

KONINIKLIJKE PHILIPS N.V. · NL

Inventors

Arne Ewald · Hamburg, DE
Frank Michael Weber · Hamburg, DE
Irina Waechter-Stehle · Hamburg, DE
Tobias Wissel · Lübeck, DE
Matthias Lenga · Mainz, DE
Jochen Peters · Norderstedt, DE

Key dates

Filing date	Dec 7, 2020
Grant date	Jul 29, 2025
Priority date	—
Expiry date	Sep 24, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG06V2201/03
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A mechanism for creating/synthesizing realistic training data, for training a machine-learning model, using anatomical knowledge. An anatomical model can be obtained. Information from annotated training data entries (i.e. “ground truth” information), can be used to model the anatomical variation, from the obtained model, in the population of the training data. This anatomical model can then be modified, e.g. incorporating some random factors, in order to generate one or more augmented models of realistic anatomies. The augmented anatomy is then transferred from the model domain to the data entry domain to thereby generate a new data entry or data entries for training a machine-learning model. This latter process can be achieved in various ways, e.g. using GANs, such as CycleGANs and label images, or deformation vector fields.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.