Accurate detection and assessment of radiation induced lung injury based on a computational model and computed tomography imaging

US10667778B2 · kind B2 · utility

Assignee

• University of Louisville Research Foundation, Inc. · US

Inventors

• Ayman S. El-Baz · Louisville, US
• Ahmed Soliman · Louisville, US
• Fahmi Khalifa · Louisville, US
• Ahmed Shaffie · Louisville, US
• Neal Dunlap · Louisville, US
• Brian Wang · Louisville, US

Key dates

• Filing date: Sep 14, 2017
• Grant date: Jun 2, 2020
• Expiry date: Oct 4, 2037

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/30061
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

A system and computation method is disclosed that identifies radiation-induced lung injury after radiation therapy using 4D computed tomography (CT) scans. After deformable image registration, the method segments lung fields, extracts functional and textural features, and classifies lung tissues. The deformable registration locally aligns consecutive phases of the respiratory cycle using gradient descent minimization of the conventional dissimilarity metric. Then an adaptive shape prior, a first-order intensity model, and a second-order lung tissues homogeneity descriptor are integrated to segment the lung fields. In addition to common lung functionality features, such as ventilation and elasticity, specific regional textural features are estimated by modeling the segmented images as samples of a novel 7th-order contrast-offset-invariant Markov-Gibbs random field (MGRF). Finally, a tissue classifier is applied to distinguish between the injured and normal lung tissues.