University of Louisville Research Foundation, Inc

Neal Dunlap

Ayman Sabry El-Baz

Ahmed Soliman

Fahmi Khalifa

Amir A Amini

Shiao Woo

Ahmed Shaffie

Brian Wang

Mohammadrreza Negahdar

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 7-order contrast-offset-invariant Markov-Gibbs random field (MGRF). Finally, a tissue classifier is applied to distinguish between the injured and normal lung tissues.

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

A method of deformable image registration for thoracic 4-D computed tomography (CT) images includes: receiving, by a processing device, a set of thoracic 4-D CT images; and iteratively solving, by the processing device, an energy function applied to subsequent images of the set of thoracic 4-D CT images to transform the subsequent images into respective optical flow fields between the subsequent images, the energy function enforcing the following constraints on the subsequent images: intensity constancy; mass conservation; gradient constancy; and spatio-temporal smoothness. A method of determining regional lung function includes: receiving, by a processing device, a set of thoracic 4-D CT images of a lung; transforming, by the processing device, the set of 4-D CT images of the lung into respective spatial voxel-wise deformation maps; and transforming, by the processing device, the spatial voxel-wise deformation maps into respective spatial voxel-wise strain maps of the lung indicating regional mechanics of the lung.

Volumetric deformable registration method for thoracic 4-D computed tomography images and method of determining regional lung function

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Louisville, KY, United States of America

Neal Dunlap