Three-dimensional motion reconstruction and analysis of the right ventricle using tagged MRI (original) (raw)

Motion analysis of the right ventricle from MRI Images

Lecture Notes in Computer Science, 1998

Both normal and abnormal right ventricular (RV) wall motion is not well understood. In this paper, we use data from tagged MRI images to perform the first 3D motion study of the entire right ventricle to date. Our technique is an adaptation of a physics-based deformable modeling methodology that was successfully used on the left ventricle(LV). As opposed to the previous approach, currently we use segmented contours to generate the geometry, 1D tags for our input data (due to the thinner RV), and localized degrees of freedom (DOFs) with finite elements. Although we build a biventricular model, our results focus on method validation and visualizing clinically useful parameters that describe RV wall motion.

Reconstruction of Detailed Left Ventricle Motion from tMRI Using Deformable Models

Lecture Notes in Computer Science, 2007

We present a system that reconstructs the 3D motion of the left ventricle (LV) for a full cardiac cycle using a deformable model built from tagged MR images. Two sets of cues are drawn from tagged MRI. The intersections of the three tagging planes, and the intersections of the LV boundary and the tagging planes, are interpolated onto the mesh vertices. We implement a deformable model to track the LV motion, utilizing Finite Element Methods (FEM) to keep the general shape and topology of the LV. This volumetric deformable model speeds up the FEM and facilitates the medical analysis. The LV motion reconstruction provides information for further analysis of cardiac mechanisms.

3D cardiac motion reconstruction from CT data and tagged MRI

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012

In this paper we present a novel method for left ventricle (LV) endocardium motion reconstruction using high resolution CT data and tagged MRI. High resolution CT data provide anatomic details on the LV endocardial surface, such as the papillary muscle and trabeculae carneae. Tagged MRI provides better time resolution. The combination of these two imaging techniques can give us better understanding on left ventricle motion. The high resolution CT images are segmented with mean shift method and generate the LV endocardium mesh. The meshless deformable model built with high resolution endocardium surface from CT data fit to the tagged MRI of the same phase. 3D deformation of the myocardium is computed with the Lagrangian dynamics and local Laplacian deformation. The segmented inner surface of left ventricle is compared with the heart inner surface picture and show high agreement. The papillary muscles are attached to the inner surface with roots. The free wall of the left ventricle in...

Deformable models with parameter functions for cardiac motion analysis from tagged MRI data

IEEE Transactions on Medical Imaging, 1996

| We present a new method for analyzing the motion of the heart's left ventricle (LV) from tagged magnetic resonance imaging (MRI) data. Our technique is based on the development of a new class of physics-based deformable models whose parameters are functions. They allow the definition of new parameterized primitives and parameterized deformations which can capture the local shape variation of a complex object. Furthermore, these parameters are intuitive and require no complex post-processing in order to be used by a physician. Using a physics-based approach, we convert the geometric models into dynamic models that deform due to forces exerted from the datapoints and conform to the given dataset. We present experiments involving the extraction of the shape and motion of the LV's mid-wall during systole from tagged MRI data based on a few parameter functions. Furthermore, by plotting the variations over time of the extracted LV model parameters from normal and abnormal heart data along the long axis, we are able to quantitatively characterize their di erences. Keywords| Physics-based modeling, Deformable models, Left ventricle (LV) shape and motion analysis and visualization.

Model-based analysis of cardiac motion from tagged MRI data

Proceedings of IEEE Symposium on Computer-Based Medical Systems (CBMS), 1994

We develop a new method for analyzing the motion of the left ventricle (LV) of a heart from tagged MRI data. Our technique is based on the development of a new class of physics-based deformable models whose parameters are functions allowing the dejinition of new parameterized primitives and parameterized deformations. These parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional twisting. Furthermore, these parameters require no complex post-processing in order to be used by a physician. Using a physics-based approach, we convert these geometric models into deformable models that deform due to forces exerted from the datapoints and conform to the given dataset. We present experiments involving the extraction of shape and motion of the LV from MRI-SPAMM data based on a few parameterfunctions. Furthermore, by plotting the variations over time of the extracted model parameters from normal and abnormal heart data we are able to characterize quantitatively their differences.

Meshless deformable models for 3D cardiac motion and strain analysis from tagged MRI

Magnetic resonance imaging, 2015

Tagged magnetic resonance imaging (TMRI) provides a direct and noninvasive way to visualize the in-wall deformation of the myocardium. Due to the through-plane motion, the tracking of 3D trajectories of the material points and the computation of 3D strain field call for the necessity of building 3D cardiac deformable models. The intersections of three stacks of orthogonal tagging planes are material points in the myocardium. With these intersections as control points, 3D motion can be reconstructed with a novel meshless deformable model (MDM). Volumetric MDMs describe an object as point cloud inside the object boundary and the coordinate of each point can be written in parametric functions. A generic heart mesh is registered on the TMRI with polar decomposition. A 3D MDM is generated and deformed with MR image tagging lines. Volumetric MDMs are deformed by calculating the dynamics function and minimizing the local Laplacian coordinates. The similarity transformation of each point is...

Analysis of left ventricular wall motion based on volumetric deformable models and MRI-SPAMM

Medical Image Analysis, 1996

We present a new approach for the analysis of the left ventricular shape and motion that is based on the development of a new class of volumetric deformable models. We estimate the deformation and complex motion of the left ventricle (LV) in terms of a few parameters that are functions and whose values vary locally across the LV. These parameters capture the radial and longitudinal contraction, the axial twisting, and the long-axis deformation. Using Lagrangian dynamics and the finite element theory, we convert these volumetric primitives into dynamic models that deform due to forces exerted by the datapoints. We present experiments where we used magnetic tagging (MIR-SPAMM) to acquire datapoints from the LV during systole. By applying our method to MRI_SPAMM datapoints, we were able to characterize both locally and globally the 3D shape and motion of the LV in a clinically useful way. In addition, based on the model parameters we were able to extract quantitative differences between normal and abnormal hearts and visualize them in a way that is useful to physicians.

3D Motion Modeling and Reconstruction of Left Ventricle Wall in Cardiac MRI

Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH, 2017

The analysis of left ventricle (LV) wall motion is a critical step for understanding cardiac functioning mechanisms and clinical diagnosis of ventricular diseases. We present a novel approach for 3D motion modeling and analysis of LV wall in cardiac magnetic resonance imaging (MRI). First, a fully convolutional network (FCN) is deployed to initialize myocardium contours in 2D MR slices. Then, we propose an image registration algorithm to align MR slices in space and minimize the undesirable motion artifacts from inconsistent respiration. Finally, a 3D deformable model is applied to recover the shape and motion of myocardium wall. Utilizing the proposed approach, we can visually analyze 3D LV wall motion, evaluate cardiac global function, and diagnose ventricular diseases.

Model-Based Shape And Motion Analysis: Left Ventricle Of A Heart

1997

The accurate and clinically useful estimation of the shape, motion, and deformation of the left ventricle of a heart (LV) is an important yet open research problem. Recently, computer vision techniques for reconstructing the 3-D shape and motion of the LV have been developed. The main drawback of these techniques, however, is that their models are formulated in terms of either too many local parameters that require non-trivial processing to be useful for close to real time diagnosis, or too few parameters to offer an adequate approximation to the LV motion.

Automatic correction of motion artifacts in 4D left ventricle model reconstructed from MRI

2014

This paper describes a computer method to correct the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data that is affected by patient motion during scanning. Three-dimensional meshes of the LV endocardial and epicardial surfaces are created from border-delineated MRI data at every time frame of the cardiac cycle to generate a time-series model of the heart. A geometrically-based approach is used to achieve smooth epicardial shapes by iterative in-plane translation of vertices in the LV model. The Principal Curvatures of the LV epicardial surfaces across multiple time frames are used to construct a shape-based optimization objective function to restore the shape of the LV via a dual-resolution semi-rigid deformation process and a free-form geometric deformation process. A limited memory quasi-Newton algorithm, L-BFGS-B, is then used to solve the optimization problem. We tested our algorithm on 9 patient-specific models and it ...