Conference Paper

Reconstruction of 3D Dense Cardiac Motion From Tagged MR Sequences.

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
DOI: 10.1109/ISBI.2004.1398679 Conference: Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA, 15-18 April 2004
Source: IEEE Xplore

ABSTRACT This paper develops an energy minimization algorithm to reconstruct the 3D motion of transplanted hearts of small animals (rats) from tagged magnetic resonance (MR) sequences. We describe the heart by a layered aggregate of thin oriented elastic fibers. We use the orientation of myocardial fibers to develop a local dense motion of the heart. This dense model is fit to the tagged MRI data by minimizing an energy functional with two terms: the first term is the external energy, derived from matching the image intensities on the fibers across two consecutive frames; the second term is the fibers' internal energy, derived from biomechanics analysis. This paper illustrates the application of the approach to a set of cardiac MR sequences containing four slices of a transplanted rat heart.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This work takes is part of a medical research project which intends to induce and study cardiac hibernation in rats. The underlying goal is to understand the physiology of heart disease. We present here a novel method to compute the 2D-deformation field of the heart (rat or human) from tagged MRI. Previous work is not suitable for wide clinical use for different reasons, including important computing time and lack of robustness. We propose an original description of tags as local minima of 1D signals. This leads us to a new formulation of the tag tracking problem as an Extrema Temporal Chaining (ETC) and a 2D-rendering. 2D-displacements are then interpolated on a dense field. The developed method is fast and robust. Its performances are compared to those of HARP, a leading method in this field.
    Advanced Concepts for Intelligent Vision Systems, 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006, Proceedings; 01/2006
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The overall objective of this project is to develop advanced techniques for scene analysis. Specifically, the problems of image registration, tracking, and change detection are considered. In this project, the following new techniques have been developed: 1) robust feature-based algorithm for object tracking, 2) motion-segmentation-based technique for change detection, 3) a target detection algorithm that consists of image differencing, maximum-margin classifier, and diversity combining, 4) a rotation-invariant transform for change detection, 5) a depth-based image registration algorithm, 6) an image registration algorithm that leverages wavelet, 7) a machine learning algorithm to automatically recover 3D surface from sparse 3D points, 8) an automatic surface fitting method for 3D reconstruction from 2D video sequence, and 9) a depth-based image registration method via geometric segmentation.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper develops an algorithm to detect abnormalities of small animals' transplanted hearts in MRI, at early stage of rejection when the hearts do not display prominent abnormal features. Existing detection methods require experts to manually identify these abnormal regions. This task is time consuming, and the detection criteria are operator dependent. We present a semi-automatic approach that needs experts to label only a small portion of the motion maps. Our algorithm begins with representing the left ventricular motions by a weighted graph that approximates the manifold where these motions lie. We compute the eigendecomposition of the Laplacian of the graph and use these as basis functions to represent the classifier. The experimental results with synthetic data and real cardiac MRI data demonstrate the application of our classifier to early detection of heart rejection
    Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA, 6-9 April 2006; 01/2006

Full-text (3 Sources)

Available from
Jun 4, 2014