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4D deformable models with temporal constraints: application to 4D cardiac image segmentation
, 2005
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2003): DREAM2S : deformable regions driven by an eulerian accurate minimization method for image and video segmentation
- International Journal of Computer Vision
"... Abstract. This paper deals with image and video segmentation using active contours. We propose a general form for the energy functional related to region-based active contours. We compute the associated evolution equation using shape derivation tools and accounting for the evolving region-based term ..."
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Cited by 50 (15 self)
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Abstract. This paper deals with image and video segmentation using active contours. We propose a general form for the energy functional related to region-based active contours. We compute the associated evolution equation using shape derivation tools and accounting for the evolving region-based terms. Then we apply this general framework to compute the evolution equation from functionals that include various statistical measures of homogeneity for the region to be segmented. Experimental results show that the determinant of the covariance matrix appears to be a very relevant tool for segmentation of homogeneous color regions. As an example, it has been successfully applied to face segmentation in real video sequences.
An Electromechanical Model of the Heart for Image Analysis and Simulation
- IEEE Transactions in Medical Imaging
"... Abstract—This paper presents a new three-dimensional electromechanical model of the two cardiac ventricles designed both for the simulation of their electrical and mechanical activity, and for the segmentation of time series of medical images. First, we present the volumetric biomechanical models bu ..."
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Cited by 45 (21 self)
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Abstract—This paper presents a new three-dimensional electromechanical model of the two cardiac ventricles designed both for the simulation of their electrical and mechanical activity, and for the segmentation of time series of medical images. First, we present the volumetric biomechanical models built. Then the transmembrane potential propagation is simulated, based on FitzHugh-Nagumo reaction-diffusion equations. The myocardium contraction is modeled through a constitutive law including an electromechanical coupling. Simulation of a cardiac cycle, with boundary conditions representing blood pressure and volume constraints, leads to the correct estimation of global and local parameters of the cardiac function. This model enables the introduction of pathologies and the simulation of electrophysiology interventions. Moreover, it can be used for cardiac image analysis. A new proactive deformable model of the heart is introduced to segment the two ventricles in time series of cardiac images. Preliminary results indicate that this proactive model, which integrates a priori knowledge on the cardiac anatomy and on its dynamical behavior, can improve the accuracy and robustness of the extraction of functional parameters from cardiac images even in the presence of noisy or sparse data. Such a model also allows the simulation of cardiovascular pathologies in order to test therapy strategies and to plan interventions. Index Terms—Cardiac image analysis, cardiac modeling, deformable model, electromechanical coupling, simulation of cardiac pathologies. I.
Construction of an abdominal probabilistic atlas and its application in segmentation
, 2003
"... There have been significant efforts to build a probabilistic atlas of the brain and to use it for many common applications, such as segmentation and registration. Though the work related to brain atlases can be applied to nonbrain organs, less attention has been paid to actually building an atlas f ..."
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Cited by 45 (3 self)
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There have been significant efforts to build a probabilistic atlas of the brain and to use it for many common applications, such as segmentation and registration. Though the work related to brain atlases can be applied to nonbrain organs, less attention has been paid to actually building an atlas for organs other than the brain. Motivated by the automatic identification of normal organs for applications in radiation therapy treatment planning, we present a method to construct a probabilistic atlas of an abdomen consisting of four organs (i.e., liver, kidneys, and spinal cord). Using 32 noncontrast abdominal computed tomography (CT) scans, 31 were mapped onto one individual scan using thin plate spline as the warping transform and mutual information (MI) as the similarity measure. Except for an initial coarse placement of four control points by the operators, the MI-based registration was automatic. Additionally, the four organs in each of the 32 CT data sets were manually segmented. The manual segmentations were warped onto the “standard ” patient space using the same transform computed from their gray scale CT data set and a probabilistic atlas was calculated. Then, the atlas was used to aid the segmentation of low-contrast organs in an additional 20 CT data sets not included in the atlas. By incorporating the atlas information into the Bayesian framework, segmentation results clearly showed improvements over a standard unsupervised segmentation method.
Soliton Dynamics in Computational Anatomy
, 2004
"... Computational Anatomy (CA) has introduced the idea of anatomical structures being transformed by geodesic deformations on groups of diffeomorphisms. Among these geometric structures, landmarks and image outlines in CA are shown to be singular solutions of a partial differential equation that is cal ..."
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Cited by 25 (8 self)
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Computational Anatomy (CA) has introduced the idea of anatomical structures being transformed by geodesic deformations on groups of diffeomorphisms. Among these geometric structures, landmarks and image outlines in CA are shown to be singular solutions of a partial differential equation that is called the geodesic EPDiff equation. A recently discovered momentum map for singular solutions of EPDiff yields their canonical Hamiltonian formulation, which in turn provides a complete parameterization of the landmarks by their canonical positions and momenta. The momentum map provides an isomorphism between landmarks (and outlines) for images and singular soliton solutions of the EPDiff equation. This isomorphism suggests a new dynamical paradigm for CA, as well as new data representation.
D.: A system for real-time XMR guided cardiovascular intervention
- IEEE TMI
, 2005
"... Abstract—The hybrid magnetic resonance (MR)/X-ray suite (XMR) is a recently introduced imaging solution that provides new possibilities for guidance of cardiovascular catheterization procedures. We have previously described and validated a technique based on optical tracking to register MR and X-ray ..."
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Cited by 23 (11 self)
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Abstract—The hybrid magnetic resonance (MR)/X-ray suite (XMR) is a recently introduced imaging solution that provides new possibilities for guidance of cardiovascular catheterization procedures. We have previously described and validated a technique based on optical tracking to register MR and X-ray images obtained from the sliding table XMR configuration. The aim of our recent work was to extend our technique by providing an improved calibration stage, real-time guidance during cardiovascular catheterization procedures, and further off-line analysis for mapping cardiac electrical data to patient anatomy. Specially designed optical trackers and a dedicated calibration object have resulted in a single calibration step that can be efficiently checked and updated before each procedure. An X-ray distortion model has been implemented that allows for distortion correction for arbitrary c-arm orientations. During procedures, the guidance
Fast Musculoskeletal Registration Based on Shape Matching
"... Abstract. This paper presents a new method for computing elastic and plastic deformations in the context of discrete deformable model-based registration. Internal forces are estimated by averaging local transforms between reference and current particle positions. Our technique can accommodate large ..."
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Cited by 19 (9 self)
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Abstract. This paper presents a new method for computing elastic and plastic deformations in the context of discrete deformable model-based registration. Internal forces are estimated by averaging local transforms between reference and current particle positions. Our technique can accommodate large non-linear deformations, and is unconditionally stable. Moreover, it is simple to implement and versatile. We show how to tune model stiffness and computational cost, which is important for efficient registration, and demonstrate our technique in the complex problem of inter-patient musculoskeletal registration. 1
Automatic Segmentation of the Left Ventricle Cavity and Myocardium in MRI Data
"... A novel approach for the automatic segmentation has been developed to extract the contours of the epi-cardium and endo-cardium boundary of the left ventricle of the heart. The developed segmentation scheme takes multi-slice and multi-phase Magnetic Resonance (MR) images of the heart, transversing th ..."
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Cited by 16 (0 self)
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A novel approach for the automatic segmentation has been developed to extract the contours of the epi-cardium and endo-cardium boundary of the left ventricle of the heart. The developed segmentation scheme takes multi-slice and multi-phase Magnetic Resonance (MR) images of the heart, transversing the short-axis length from the base to the apex. Each image is taken at one instance in the heart’s phase. The images are segmented using a diffusion-based filter followed by an unsupervised clustering technique and the resulting labels are checked to locate the left ventricle (lv) cavity. From cardiac anatomy, the closest pool of blood to the lv cavity is the right ventricle cavity. The wall between these two blood-pools (interventricular septum) is measured to give an approximate thickness for the myocardium. This value is used when a radial search is performed on a gradient image to find appropriate robust segments of the epi-cardium boundary. The robust edge segments are then joined using a normal spline curve. Experimental results are presented with very encouraging qualitative and quantitative results and a comparison is made against the state-of-the art level-sets method.
Automated Segmentation of the Prostate in 3D MR Images Using a Probabilistic Atlas and a Spatially Constrained Deformable Model
, 2010
"... Purpose: We present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. Method: Our approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a com ..."
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Cited by 15 (0 self)
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Purpose: We present a fully automatic algorithm for the segmentation of the prostate in three-dimensional magnetic resonance (MR) images. Method: Our approach requires the use of an anatomical atlas which is built by computing transformation fields mapping a set of manually segmented images to a common reference. These transformation fields are then applied to the manually segmented structures of the training set in order to get a probabilistic map on the atlas. The segmentation is then realized through a two stage procedure. In the first stage, the processed image is registered to the probabilistic atlas. Subsequently, a probabilistic segmentation is obtained by mapping the probabilistic map of the atlas to the patient’s anatomy. In the second stage, a deformable surface evolves towards the prostate boundaries by merging information coming from the probabilistic segmentation, an image feature model and a statistical shape model. Duringtheevolution ofthesurface, the probabilistic segmentation allows the introduction of a spatial constraint that prevents the deformable surface from leaking in an unlikely configuration. Results: The proposed method is evaluated on 36 exams, that were manually segmented by a single expert. A median Dice similarity coefficient of 0.86 and an average surface error of 2.41 mm are achieved. Conclusion: By merging prior knowledge, thepresentedmethodachievesarobustandcompletely automatic segmentation of the prostate in MR images. Results show that the use of a spatial constraint isusefultoincreasetherobustness of the deformable model comparatively to a deformable surface that is only driven by an image appearance model.
Epidaure: a Research Project in Medical Image Analysis, Simulation and Robotics at INRIA
, 2003
"... INTRODUCTION E PIDAURE is the name of a research project launched in 1989 at INRIA Rocquencourt, close to Paris, France. At that time, after a first experience of research in Computer Vision [1] in the group of O. Faugeras, I was very enthusiastic about the idea of transposing research resul ..."
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Cited by 15 (4 self)
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INTRODUCTION E PIDAURE is the name of a research project launched in 1989 at INRIA Rocquencourt, close to Paris, France. At that time, after a first experience of research in Computer Vision [1] in the group of O. Faugeras, I was very enthusiastic about the idea of transposing research results of digital image analysis into the medical domain. Visiting hospitals and medical research centers, I was progressively convinced that Medical Image Analysis was an important research domain by itself. In fact I had the impression that a better exploitation of the available medical imaging modalities would require more and more advanced image processing tools in the short and long-term future, not only to assess the diagnosis on more objective and quantitative measurements, but also to better prepare, control and evaluate the therapy. Fig. 1. This image has been the "Logo" of the Epidaure project for a long time. It was also used as a logo of the first CVRMed Conference held in Nice in 1
