Leland Stanford Junior University

Matthew Lungren

Andrew Y Ng

Pranav Rajpurkar

Amirhossein Kiani

Nguyet Minh Phu

Chris Wang

Mark Sabini

Sharon Zhou

Jeremy Irvin

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.

Systems and methods for radiology image classification from noisy images

Growing community of inventors

Stanford, CA, United States of America

Matthew Lungren