Identifying calcification lesions in contrast enhanced images

US12020429B2 · kind B2 · utility

Assignee

• Nano-X Al Ltd. · IL

Inventors

• Ronen Marc Gordon · Tel Mond, IL
• Amir Bar · Rehovot, IL
• Raouf Muhamedrahimov · San Francisco, US
• Ayelet Akselrod-Ballin · Kiryat Ono, IL

Key dates

• Filing date: Jun 17, 2021
• Grant date: Jun 25, 2024
• Expiry date: Jul 2, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/30101
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

There is provided a method of training a machine learning model, comprising: for each set of sample medical images depicting calcification within a target anatomical structure wherein each set includes non-contrast medical image(s) and contrast enhanced medical image(s), correlating between calcifications depicted in the target anatomical structure of the contrast enhanced image(s) with corresponding calcifications depicted in the target anatomical structure of the non-contrast medical image(s), computing calcification parameter(s) for calcification depicted in the respective target anatomical structure, labelling each contrast enhanced medical image with the calcification parameter(s), and training the machine learning model on a training dataset that includes the contrast enhanced medical images of the sets, each labelled with ground truth label of a respective calcification parameter(s), for generating an outcome indicative of a target calcification parameter(s) for calcification depicted in the target anatomical structure of a target contrast enhanced medical image provided as input.