Pengcheng Shi

Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery

Non-rigid motion estimation from image sequences is essential in analyzing and understanding the dynamic behavior of physical objects. One important example is the dense field motion analysis of the cardiac wall, which could potentially help to better understand the physiological processes associated with heart disease and to provide improvement in patient diagnosis and treatment. In this paper, we present a new method of estimating volumetric deformation by integrating intrinsic instantaneous velocity data with geometrical token displacement information, based upon continuum mechanics principles. This object-dependent approach allows the incorporation of physically meaningful constraints into the ill-posed motion recovery problem, and the integration of the two disparate but complementary data sources overcomes some of the limitations of the single-image-source-based motion estimation approaches.

A model-based integrated approach to track myocardial deformation using displacement and velocity constraints

Accurate estimation of heart wall dense field motion and deformation could help to better understand the physiological processes associated with ischemic heart diseases, and to provide significant improvement in patient treatment. We present a new method of estimating left ventricular deformation which integrates instantaneous velocity information obtained within the mid-wall region with shape information found on the boundaries of the left ventricle. Velocity information is obtained from phase contrast magnetic resonance images, and boundary information is obtained from shape-based motion tracking of the endo- and cardial boundaries. The integration takes place within a continuum biomechanical heart model which is embedded in a finite element framework. We also employ a feedback mechanism to improve tracking accuracy. The integration of the two disparate but complementary sources overcomes some of the limitations of previous work in the field which concentrates on motion estimation from a single image-derived source.<<ETX>>

Myocardial motion and function assessment using 4D images

This paper describes efforts aimed at more objectively and accurately quantifying the local, regional and global function of the left ventricle (LV) of the heart from 4D image data. Using our shape-based image analysis methods, point-wise myocardial motion vector fields between successive image frames through the entire cardiac cycle will be computed. Quantitative LV motion, thickening, and strain measurements will then be established from the point correspondence maps. In the paper, we will also briefly describe an in vivo experimental model which uses implanted imaging-opaque markers to validate the results of our image analysis methods. Finally, initial experimental results using image sequences from two different modalities will be presented.

A Unified Framework to Assess Myocardial Function from 4D Images

This paper describes efforts aimed at developing a unified framework to more accurately quantify the local, regional and global function of the left ventricle (LV) of the heart, under both normal and ischemic conditions, using four—dimensional (4D) imaging data over the entire cardiac cycle. The approach incorporates motion information derived from the shape properties of the endocardial and epicardial surfaces of the LV, as well as mid—wall 3D instantaneous velocity information from phase contrast MR images, and/or mid—wall displacement information from tagged MR images. The integration of the disparate but complementary sources of information overcomes the limitations of previous work which concentrates on motion estimation from a single image—derived source. 1

Physical and geometrical modeling for image-based recovery of left ventricular deformation

Information about left ventricular (LV) mechanical performance is of critical importance in understanding the etiology of ischemic heart disease. Regional measurements derived from non-invasive imaging to assist in assessing this performance have been in use for decades, and certain parameters derived from these measurements often are useful clinically, as they correlate to some extent with gross physiological hypotheses. However, relatively little work has been done to date to carefully understand the relationship of regional myocardial injury to the local mechanical performance of the heart as derived from image data acquired non-invasively for a particular patient in 3 spatial dimensions over time. This paper describes efforts to take advantage of recent developments in 3D non-invasive imaging and biomechanical modeling to design an integrated computational platform capable of assembling a variety of displacement and velocity data derived from each image frame to deform a volumetric model representation of a portion of the myocardium. A brief description of the reasoning behind this strategy an overview of the approach and some initial results are described.

Toward reliable, noninvasive measurement of myocardial function from 4D images

This paper describes efforts aimed at more accurately and objectively determining and quantifying the local, regional, and global function of the left ventricle (LV) of the heart under both normal and ischemic conditions. These measurements and evaluations are made using non-invasive, 3-D, cardiac diagnostic imaging sequences (i.e., 4-D data) and rely on an approach that follows the shape properties of the endocardial and epicardial surfaces of the LV over the entire cardiac cycle. Our efforts involve the development of an acute infarct animal model that permits us to establish the validity of our noninvasive image analysis algorithms, as well as permits us to study the efficacy of using in vivo, image-derived measures of function for predicting regional myocardial viability (immediately post mortem). We first describe the experimental setup for the animal model, including the use of implanted imaging-opaque markers that assist in setting up a gold standard against which image-derived measurements can be evaluated. Next, the imaging techniques are described, and finally the image analysis methods and their comparison to the validation technique are discussed.

Three-dimensional regional left ventricular deformation from digital sonomicrometry

Understanding how the left ventricle deforms in 3D and how this deformation is altered with coronary occlusion may lead to the development of non-invasive imaging techniques to determine the extent of permanent injury. To determine regional 3D strains in the left ventricle of the heart the authors employed digital sonomicrometry, with high temporal and spatial resolution. Two cubic arrays of 8 omnidirectional transceiver crystals were implanted in two regions of the left ventricle in an open chest canine preparation (n=6). Additional crystals were used to define a fixed external reference space and the long axis of the ventricle. Using ultrasound transit time the distances between all the crystals were recorded. A multidimensional scaling technique was then applied to transform the distances to 3D crystal coordinates. A least squares fit of the displacement field was applied to calculate homogeneous strains for each cube. Cardiac specific directions were determined and strains rotated into the local coordinate space. This technique was applied pre- and post- coronary occlusion. Alterations in strain patterns were evident in the ischemic region and subtle temporal changes in the control region. Thus, digital sonomicrometry, with high temporal and spatial resolution, enhances ones ability to analyze regional left ventricular 3D strain patterns.

Image processing and analysis for medical applications

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Motion tracking of the left-ventricular surface

A framework for tracking the motion of surfaces with specific applications to the left- ventricular endocardial wall is outlined. We use an elastic model of the object with constraints on the types of motion for tracking the movement. Conformal stretching is measured from a system of coordinates based on the principal directions of a surface patch, and in addition, an energy for bending of a 3-D surface is defined. Once initial match vectors are obtained from the bending and stretching model, membrane smoothing with confidences optimizes the flow estimates. To this end, a linear vector equation in terms of components of flow vectors is derived which must be satisfied at all nodes of a finite element grid. The coupled system of equations are solved with relaxation techniques. Applications of the algorithms to real and simulated data are given at the end.