Biomedical subjects

Amir A Amini

Publications and source records attributed to Amir A Amini.

6 recordsLinked to original sources

PubMed2006

Biventricular myocardial strains via nonrigid registration of anatomical NURBS model [corrected].

We present research in which both left and right ventricular deformation is estimated from tagged cardiac magnetic resonance imaging using volumetric deformable models constructed from nonuniform rational B-splines (NURBS). The four model types considered and compared for the left ventricle include two Cartesian NURBS models--one with a cylindrical parameter assignment and one with a prolate spheroidal parameter assignment. The remaining two are non-Cartesian, i.e., prolate spheroidal and cylindrical each with their respective prolate spheroidal and cylindrical parameter assignment regimes. These choices were made based on the typical shape of the left ventricle. For each frame starting with end-diastole, a NURBS model is constructed by fitting two surfaces with the same parameterization to the corresponding set of epicardial and endocardial contours from which a volumetric model is created. Using normal displacements of the three sets of orthogonal tag planes as well as displacements of contour/tag line intersection points and tag plane intersection points, one can solve for the optimal homogeneous coordinates, in a weighted least squares sense, of the control points of the deformed NURBS model at end-diastole using quadratic programming. This allows for subsequent nonrigid registration of the biventricular model at end-diastole to all later time frames. After registration of the model to all later time points, the registered NURBS models are temporally lofted in order to create a comprehensive four-dimensional NURBS model. From the lofted model, we can extract three-dimensional myocardial deformation fields and corresponding Lagrangian and Eulerian strain maps which are local measures of nonrigid deformation. The results show that, in the case of simulated data, the quadratic Cartesian NURBS models with the cylindrical and prolate spheroidal parameter assignments outperform their counterparts in predicting normal strain. The decreased complexity associated with the Cartesian model with the cylindrical parameter assignment prompted its use for subsequent calculations. Lagrangian strains in three canine data, a normal human, and a patient with history of myocardial infarction are presented. Eulerian strains for the normal human data are also included.

Algorithms↗

PubMed2004

Factors affecting the accuracy of pressure measurements in vascular stenoses from phase-contrast MRI.

In this work the effects of noise, resolution, and velocity (flow) on the measurement of intravascular pressure from phase-contrast (PC) MRI are discussed. To elucidate these effects, we employed an axisymmetric geometry that enabled us to calculate pressures in <2 min on a Sun Ultra SPARC 10 workstation. To determine the effects of vascular stenoses, we fabricated several stenotic phantom geometries (with 50%, 75%, and 90% area stenoses), and performed both MRI and computational fluid dynamics (CFD) simulations for various flow rates for these phantom geometries. Noise with Gaussian statistics was added to the velocity field obtained from the CFD simulations. The pressure maps obtained directly from CFD simulations for our phantom geometries were compared with pressure maps derived by our algorithm when 1) the input was noise-corrupted velocity data from CFD, and 2) the input was PC-MRI data collected from the phantoms. The quantitative effects of noise, resolution, and flow rate on the accuracy of pressure measurements were determined. We found that for flow rates below the Reynolds number for turbulent flow, resolution is a more significant determinant of accuracy than SNR. Furthermore, if other parameters remain constant, increased flow rates may result in decreased accuracy.

Algorithms↗

PubMed2004

Quantifying 3-D vascular structures in MRA images using hybrid PDE and geometric deformable models.

The aim of this paper is to present a hybrid approach to accurate quantification of vascular structures from magnetic resonance angiography (MRA) images using level set methods and deformable geometric models constructed with 3-D Delaunay triangulation. Multiple scale filtering based on the analysis of local intensity structure using the Hessian matrix is used to effectively enhance vessel structures with various diameters. The level set method is then applied to automatically segment vessels enhanced by the filtering with a speed function derived from enhanced MRA images. Since the goal of this paper is to obtain highly accurate vessel borders, suitable for use in fluid flow simulations, in a subsequent step, the vessel surface determined by the level set method is triangulated using 3-D Delaunay triangulation and the resulting surface is used as a parametric deformable model. Energy minimization is then performed within a variational setting with a first-order internal energy; the external energy is derived from 3-D image gradients. Using the proposed method, vessels are accurately segmented from MRA data.

Algorithms↗

PubMed2003

Myocardial kinematics from tagged MRI based on a 4-D B-spline model.

Current research investigating the modeling of left ventricular dynamics for accurate clinical assessment of cardiac function is extensive. Magnetic resonance (MR) tagging is a functional imaging method which allows for encoding of a grid of signal voids on cardiac MR images, providing a mechanism for noninvasive measurement of intramural tissue deformations, in vivo. We present a novel technique of employing a four-dimensional (4-D) B-spline model which permits concurrent determination of myocardial beads and myocardial strains. The method entails fitting the knot planes of the 4-D B-spline model for fixed times to a sequence of triplets of orthogonal sets of tag surfaces for all imaged volumetric frames within the constraints of the model's spatio-temporal internal energy. From a three-dimensional (3-D) displacement field, the corresponding long and short-axis Lagrangian normal, shear, and principal strain maps are produced. As an important byproduct, the points defined by the 3-D intersections of the triplets of orthogonal tag planes, which we refer to as myocardial beads, can easily be determined by our model. Displaying the beads as a movie loop allows for the visualization of the nonrigid movement of the left ventricle in 3-D.

Algorithms↗

PubMed2003

Regularization of flow streamlines in multislice phase-contrast MR imaging.

Magnetic resonance angiography (MRA) has become an important tool for the clinical evaluation of vascular disease. Flow measurement with phase-contrast (PC) magnetic resonance (MR) imaging provides a powerful method for evaluation of blood velocity information inside vessels. However, image artifacts from complex flow patterns including slow flow, recirculation zone, and pulsatile flow can adversely affect accuracy of results. In this paper, we introduce a new numerical formulation for improving the accuracy of PC velocity fields and corresponding streamlines, based on a physical constraint from fluid dynamics, within a regularization framework. The formulation which makes use of a stream function, automatically enforces continuity constraint of incompressible flow and reconstructs the flow streamlines from PC images. We applied the algorithm to complex MR imaging flow velocities obtained in a flow phantom of an axisymmetric abdominal aortic aneurysm. The algorithm significantly improved streamline results especially inside the recirculation zone, where artifacts are more pronounced. A velocity reconstruction method in primitive variable form is also presented and results are compared with the stream function method. In order to validate flow characteristics derived from PC MR images, we used the FLUENT computational fluid dynamics software package, to simulate flow patterns within the same geometry as our phantom. There was a good agreement between the numerical simulations and recovered PC streamline results. Processed streamlines, in both stream function and primitive variable methods, were more realistic and provided more precise flow patterns than unprocessed PC data. Additionally, the feasibility of the method was demonstrated in the aorta of a normal volunteer.

Algorithms↗

PubMed2002

A MAP framework for tag line detection in SPAMM data using Markov random fields on the B-spline solid.

Magnetic resonance (MR) tagging is a technique for measuring heart deformations through creation of a stripe grid pattern on cardiac images. In this paper, we present a maximum a posteriori (MAP) framework for detecting tag lines using a Markov random field (MRF) defined on the lattice generated by three-dimensional (3-D) and four-dimensional (4-D) (3-D + t) uniform sampling of B-spline models. In the 3-D case, MAP estimation is cast for detecting present tag features in the current image given an initial solid from the previous frame (the initial undeformed solid is manually positioned by clicking on corner points of a cube). The method also allows the parameters of the solid model, including the number of knots and the spline order, to be adjusted within the same framework. Fitting can start with a solid with less knots and lower spline order and proceed to one with more knots and/or higher order so as to achieve more accuracy and/or higher order of smoothness. In the 4-D case, the initial model is considered to be the linear interpolation of a sequence of optimal solids obtained from 3-D tracking. The same framework proposed for the 3-D case can once again be applied to arrive at a 4-D B-spline model with a higher temporal order.

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