Howard University

John M M Anderson

Mandoye Ndoye

Oludotun Ode

Henry C Ogworonjo

A myocardial blood flow analysis scan includes incorporating a pharmacological kinetic model with the standard factor analysis model where each time activity curve is assumed to be a linear combination of factor curves. Pharmacological kinetics based factor analysis of dynamic structures (K-FADS-II) model can be applied, whereby estimating factor curves in the myocardium can be physiologically meaningful is provided. Additional optional aspects include performing a discretization to transform continuous-time K-FADS-II model into a discrete-time K-FADS-II model and application of an iterative Improved Voxel-Resolution myocardial blood flow (IV-MBF) algorithm. Where the model is applied without assumption that a right ventricle tissue curve and a left ventricle tissue curve obey a particular mathematical relationship, a least squares objective function can be applied to obtain estimates for parameters of the pharmacological kinetic model by applying a majorize-minimize optimization technique to iteratively estimate the curves.

Voxel-resolution myocardial blood flow analysis

A majorize-minimize (MM) mathematical principle is applied to least squares regularization estimation problems to effect efficient processing of image data sets to provide good quality images. In a ground penetrating radar application, these approaches can reduce processing time and memory use by accounting for a symmetric nature of a given radar pulse, accounting for similar discrete time delays between transmission of a given radar pulse and reception of reflections from the given radar pulse, and accounting for a short duration of the given radar pulse.

Using an MM-principle to achieve fast image data estimation from large image data sets

The mathematical majorize-minimize principle is applied in various ways to process the image data to provide a more reliable image from the backscatter data using a reduced amount of memory and processing resources. A processing device processes the data set by creating an estimated image value for each voxel in the image by iteratively deriving the estimated image value through application of a majorize-minimize principle to solve a maximum a posteriori (MAP) estimation problem associated with a mathematical model of image data from the data. A prior probability density function for the unknown reflection coefficients is used to apply an assumption that a majority of the reflection coefficients are small. The described prior probability density functions promote sparse solutions automatically estimated from the observed data.

Using an MM-principle to enforce a sparsity constraint on fast image data estimation from large image data sets

A myocardial blood flow analysis scan includes incorporating a pharmacological kinetic model with the standard factor analysis model where each time activity curve is assumed to be a linear combination of factor curves. Pharmacological kinetics based factor analysis of dynamic structures (K-FADS) model can be applied, whereby a means for estimating factor curves in the myocardium that are physiologically meaningful is provided. Additional optional aspects include performing a discretization to transform continuous-time K-FADS model into a discretetime K-FADS model and application of an iterative Voxel-Resolution myocardial blood flow (V-MBF) algorithm. A V-MBF algorithm based on a model that accounts for the fact that the shape of TACs due to ischemic and normal tissue are different can be included.

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Washington, DC, United States of America

John M M Anderson