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Author |
Joel Barajas; Jaume Garcia; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
Angle Images Using Gabor Filters in Cardiac Tagged MRI |
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Conference Article |
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2005 |
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Proceeding of the 2005 conference on Artificial Intelligence Research and Development |
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107-114 |
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Angle Images, Gabor Filters, Harp, Tagged Mri |
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Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results. |
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Amsterdam; The Netherlands |
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IOS Press |
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Amsterdam, The Netherlands |
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1-58603-560-6 |
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BCNPCL @ bcnpcl @ BGC2005; IAM @ iam |
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595 |
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Author |
Jaume Garcia; Albert Andaluz; Debora Gil; Francesc Carreras |
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Title |
Decoupled External Forces in a Predictor-Corrector Segmentation Scheme for LV Contours in Tagged MR Images |
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Conference Article |
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2010 |
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32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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4805-4808 |
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Computation of functional regional scores requires proper identification of LV contours. On one hand, manual segmentation is robust, but it is time consuming and requires high expertise. On the other hand, the tag pattern in TMR sequences is a problem for automatic segmentation of LV boundaries. We propose a segmentation method based on a predictorcorrector (Active Contours – Shape Models) scheme. Special stress is put in the definition of the AC external forces. First, we introduce a semantic description of the LV that discriminates myocardial tissue by using texture and motion descriptors. Second, in order to ensure convergence regardless of the initial contour, the external energy is decoupled according to the orientation of the edges in the image potential. We have validated the model in terms of error in segmented contours and accuracy of regional clinical scores. |
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Buenos Aires (Argentina) |
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IEEE EMB |
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1557-170X |
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978-1-4244-4123-5 |
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IAM @ iam @ GAG2010 |
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1514 |
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Joel Barajas; Jaume Garcia; Karla Lizbeth Caballero; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
Correction of Misalignment Artifacts Among 2-D Cardiac MR Images in 3-D Space |
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Conference Article |
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2006 |
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1st International Wokshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII’06) |
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3217 |
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114-121 |
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Cardiac Magnetic Resonance images offer the opportunity to study the heart in detail. One of the main issues in its modelling is to create an accurate 3-D reconstruction of the left ventricle from 2-D views. A first step to achieve this goal is the correct registration among the different image planes due to patient movements. In this article, we present an accurate method to correct displacement artifacts using the Normalized Mutual Information. Here, the image views are treated as planes in order to diminish the approximation error caused by the association of a certain thickness, and moved simultaneously to avoid any kind of bias in the alignment process. This method has been validated using real and syntectic plane displacements, yielding promising results. |
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Copenhagen (Denmark) |
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978-3-540-22977-3 |
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IAM @ iam @ BGC2006 |
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1485 |
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Author |
Debora Gil; Jaume Garcia; Mariano Vazquez; Ruth Aris; Guilleaume Houzeaux |
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Title |
Patient-Sensitive Anatomic and Functional 3D Model of the Left Ventricle Function |
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Conference Article |
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2008 |
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8th World Congress on Computational Mechanichs (WCCM8) |
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Left Ventricle, Electromechanical Models, Image Processing, Magnetic Resonance. |
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Early diagnosis and accurate treatment of Left Ventricle (LV) dysfunction significantly increases the patient survival. Impairment of LV contractility due to cardiovascular diseases is reflected in its motion patterns. Recent advances in medical imaging, such as Magnetic Resonance (MR), have encouraged research on 3D simulation and modelling of the LV dynamics. Most of the existing 3D models [1] consider just the gross anatomy of the LV and restore a truncated ellipse which deforms along the cardiac cycle. The contraction mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fibers. It follows that such simplified models do not allow evaluation of the heart electro-mechanical function and coupling, which has recently risen as the key point for understanding the LV functionality [2]. In order to thoroughly understand the LV mechanics it is necessary to consider the complete anatomy of the LV given by the orientation of the myocardial fibres in 3D space as described by Torrent Guasp [3].
We propose developing a 3D patient-sensitive model of the LV integrating, for the first time, the ven- tricular band anatomy (fibers orientation), the LV gross anatomy and its functionality. Such model will represent the LV function as a natural consequence of its own ventricular band anatomy. This might be decisive in restoring a proper LV contraction in patients undergoing pace marker treatment.
The LV function is defined as soon as the propagation of the contractile electromechanical pulse has been modelled. In our experiments we have used the wave equation for the propagation of the electric pulse. The electromechanical wave moves on the myocardial surface and should have a conductivity tensor oriented along the muscular fibers. Thus, whatever mathematical model for electric pulse propa- gation [4] we consider, the complete anatomy of the LV should be extracted.
The LV gross anatomy is obtained by processing multi slice MR images recorded for each patient. Information about the myocardial fibers distribution can only be extracted by Diffusion Tensor Imag- ing (DTI), which can not provide in vivo information for each patient. As a first approach, we have
Figure 1: Scheme for the Left Ventricle Patient-Sensitive Model.
computed an average model of fibers from several DTI studies of canine hearts. This rough anatomy is the input for our electro-mechanical propagation model simulating LV dynamics. The average fiber orientation is updated until the simulated LV motion agrees with the experimental evidence provided by the LV motion observed in tagged MR (TMR) sequences. Experimental LV motion is recovered by applying image processing, differential geometry and interpolation techniques to 2D TMR slices [5]. The pipeline in figure 1 outlines the interaction between simulations and experimental data leading to our patient-tailored model. |
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Venice; Italy |
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9788496736559 |
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IAM @ iam @ GGV2008b |
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993 |
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