Machine learning based processing of magnetic resonance data, including an uncertainty quantification

US11965946B2 · kind B2 · utility

Assignee

• Max-Planck-Gesellschaft zur Föderung der Wissenschaften e.V. · US

Inventors

• Moritz Zaiss · Erlangen, DE
• Felix Glang · Rötteln, DE
• Sergey V. Prokudin · Tübingen, DE
• Klaus Scheffler · Basel, CH

Key dates

• Filing date: Dec 4, 2020
• Grant date: Apr 23, 2024
• Expiry date: May 20, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/30096
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

A method of processing magnetic resonance data of a sample under investigation includes the steps of provision of the MR data being collected with an MRI scanner apparatus, and machine learning based data analysis of the MR data by supplying the MR data to an artificial neural network being trained with predetermined training data, wherein at least one image parameter of the sample and additionally at least one uncertainty quantification measure representing a prediction error of the at least one image parameter are provided by output elements of the neural network. Furthermore, a magnetic resonance imaging (MRI) scanner apparatus being adapted for employing the method of processing MR data is described.