Full dose PET image estimation from low-dose PET imaging using deep learning

US11576628B2 · kind B2 · utility

Assignee

• KONINIKLIJKE PHILIPS N.V. · NL

Inventors

• Sydney Kaplan · Highland Heights, US
• Yang Zhu · Solon, US
• Andriy ANDREYEV · Willoughby Hills, US
• Chuanyong Bai · Poway, US
• Steven M. Cochoff · Chagrin Falls, US

Key dates

• Filing date: Dec 26, 2018
• Grant date: Feb 14, 2023
• Expiry date: Nov 14, 2039

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/20084
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

Emission imaging data are reconstructed to generate a low dose reconstructed image. Standardized uptake value (SUV) conversion (30) is applied to convert the low dose reconstructed image to a low dose SUV image. A neural network (46, 48) is applied to the low dose SUV image to generate an estimated full dose SUV image. Prior to applying the neural network the low dose reconstructed image or the low dose SUV image is filtered using a low pass filter (32). The neural network is trained on a set of training low dose SUV images and corresponding training full dose SUV images to transform the training low dose SUV images to match the corresponding training full dose SUV images, using a loss function having a mean square error loss component (34) and a loss component (36) that penalizes loss of image texture and/or a loss component (38) that promotes edge preservation.