Machine learning for automatic detection of intracranial hemorrhages with uncertainty measures from medical images

US12112844B2 · kind B2 · utility

Assignee

• Siemens Healthineers AG · DE

Inventors

• Eli Gibson · Plainsboro, US
• Bogdan Georgescu · Plainsboro, US
• Pascal Ceccaldi · New York, US
• Youngjin Yoo · Princeton, US
• Jyotipriya Das · Plainsboro, US
• Thomas Re · Monroe, US
• Eva Eibenberger · Nuremberg, DE
• Andrei Chekkoury · Erlangen, DE
• Barbara Brehm · Forchheim, DE
• Thomas Flohr · Uehlfeld, DE
• Dorin Comaniciu · Princeton Junction, US
• Pierre-Hugo Trigan · Le Mesnil, FR

Key dates

• Filing date: Mar 12, 2021
• Grant date: Oct 8, 2024
• Expiry date: Jun 23, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/30
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Systems and method for performing a medical imaging analysis task for making a clinical decision are provided. One or more input medical images of a patient are received. A medical imaging analysis task is performed from the one or more input medical images using a machine learning based network. The machine learning based network generates a probability score associated with the medical imaging analysis task. An uncertainty measure associated with the probability score is determined. A clinical decision is made based on the probability score and the uncertainty measure.