Johnson & Johnson Enterprise Innovation Inc.

The Brigham and Women's Hospital, Inc.

George R Washko

Christopher Scott Stevenson

Samuel Yoffe Ash

Matthew David Mailman

Raul San Jose Estepar

Ron Kikinis

Carl-Fredrik Westin

Raúl San José Estépar

Edwin K Silverman

John J Reilly

Risk prediction models are trained and deployed to analyze images, such as computed tomography scans, for predicting risk of lung cancer (e.g., current or future risk of lung cancer) for one or more subjects. Individual risk prediction models are trained on nodule-specific and non-nodule specific features, including longitudinal nodule specific and longitudinal non-nodule specific features, such that each risk prediction model can predict risk of lung cancer across different time horizons. Such risk prediction models are useful for developing preventive therapies for lung cancer by enabling clinical trial enrichment.

System and method for predicting the risk of future lung cancer

Risk prediction models are trained and deployed to analyze images, such as computed tomography scans, for predicting future risk of lung cancer for one or more subjects. Individual risk prediction models are separately trained on nodule-specific and non-nodule specific features such that each risk prediction model can predict future risk of lung cancer across different time periods (e.g., 1 year, 3 years, or 5 years). Such risk prediction models are useful for developing preventive therapies for lung cancer by enabling clinical trial enrichment.

A method for reconstructing an image includes receiving tomographic data representative of an image signal; deriving, from the image signal, a plurality of components; identifying a spatial location associated with maximum phase congruency of the components; incorporating, into an image, an edge at the spatial location; and providing an output representative of the image.

Measurement of thin-layered structures in X-ray computer tomography

Growing community of inventors

West Roxbury, MA, United States of America

George R Washko