Systems and methods for radiology image classification from noisy images

US11798159B2 · kind B2 · utility

Assignee

• The Board of Trustees of the Leland Stanford Junior University · US

Inventors

• Sharon Zhou · Stanford, US
• Andrew Yan-Tak Ng · Palo Alto, US
• Pranav Rajpurkar · Stanford, US
• Mark William Sabini · River Edge, US
• Chris Wang · Taipei, TW
• Nguyet Minh Phu · Stanford, US
• Amirhossein Kiani · Stanford, US
• Jeremy Irvin · Stanford, US
• Matthew Lungren · Stanford, US

Key dates

• Filing date: Sep 18, 2020
• Grant date: Oct 24, 2023
• Expiry date: Oct 8, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/30048
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Systems and methods for radiology image classification from noisy images in accordance with embodiments of the invention are illustrated. One embodiment includes noisy image classification device, including a processor, camera circuitry, and a memory containing a noisy image classification application, where the noisy image classification application directs the processor to obtain image data describing a first image taken of a second image using the camera circuitry, where the second image was produced by a medical imaging device, and where the first image is a noisy version of the second image, classify the image data using a neural network trained to be robust to noise, generate an investigation recommendation based on the classification, and provide the investigation recommendation via a display.