Assessment of abnormality patterns associated with COVID-19 from x-ray images

US11717233B2 · kind B2 · utility

Assignee

• Siemens Healthcare Limited · DE

Inventors

• Florin-Cristian Ghesu · Erlangen, DE
• Siqi LIU · Dongguan, CN
• Awais Mansoor · Potomac, US
• Sasa Grbic · Plainsboro, US
• Sebastian Vogt · Jena, DE
• Dorin Comaniciu · Princeton Junction, US
• Ruhan Sa · Monmouth Junction, US
• Zhoubing Xu · Plainsboro, US

Key dates

• Filing date: Jul 21, 2020
• Grant date: Aug 8, 2023
• Expiry date: Sep 17, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V2201/031
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Systems and methods for assessing a disease are provided. An input medical image in a first modality is received. Lungs are segmented from the input medical image using a trained lung segmentation network and abnormality patterns associated with the disease are segmented from the input medical image using a trained abnormality pattern segmentation network. The trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality patterns.