this article describes a methodology for creating a generic volumetric biomechanical model from different image modalities and segmenting time series of medicalimages using this model. the construction of such a gene...
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this article describes a methodology for creating a generic volumetric biomechanical model from different image modalities and segmenting time series of medicalimages using this model. the construction of such a generic model consists of three stages: geometric meshing. non-rigid deformation of the mesh in images of various modalities, and image-to-mesh information mapping through rasterization. the non-rigid deformation stage, which relies on a combination of global and local deformations, can then be used to segment time series of images. e.g. cine MRI or gated SPECT cardiac images. We believe that this type of deformable biomechanical model can play an important role in the extraction of useful quantitative local parameters of cardiac function. the biomechanical model of the heart will be coupled with an electrical model of another collaborative project in order to simulate and analyze a larger class of pathologies. (C) 2003 Elsevier B.V. All rights reserved.
In this paper, a system for fully automatic planning of short-axis (SA) cardiac MR acquisition is evaluated. Experimental results from 11 patients and 3 healthy subjects show that the difference between the automatic ...
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ISBN:
(数字)9783540399032
ISBN:
(纸本)3540204644
In this paper, a system for fully automatic planning of short-axis (SA) cardiac MR acquisition is evaluated. Experimental results from 11 patients and 3 healthy subjects show that the difference between the automatic and manual planning was not statistically significant.
We propose a novel approach to landmark-based medicalimage registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistical relation between two images, as estimated usi...
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ISBN:
(纸本)3540204644
We propose a novel approach to landmark-based medicalimage registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistical relation between two images, as estimated using general-purpose registration algorithms, in order to construct an optimum predictor of the displacement field. High accuracy is achieved by using an estimated spatial model of the displacement field directly from the image data, while practically circumventing the difficulties that prevented Kriging from being widely used in image registration.
In the automatic se-mentation of echocardiographic images, a priori shape knowledge has been used to compensate for poor features in ultrasound images. this shape knowledge is often learned via an off-line training pr...
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In the automatic se-mentation of echocardiographic images, a priori shape knowledge has been used to compensate for poor features in ultrasound images. this shape knowledge is often learned via an off-line training process, which requires tedious human effort and is highly expertise-dependent. More importantly, a learned shape template can only be used to segment a specific class of images with similar boundary shape. In this paper, we present a multi-scale level set framework for segmentation of endocardial boundaries at each frame in a multiframe echocardiographic image sequence. We point out that the intensity distribution of an ultrasound image at a very coarse scale can be approximately modeled by Gaussian. then we combine region homogeneity and edge features in a level set approach to extract boundaries automatically at this coarse scale. At finer scale levels, these coarse boundaries are used to both initialize boundary detection and serve as an external constraint to guide contour evolution. this constraint functions similar to a traditional shape prior. Experimental results validate this combinative framework. (C) 2003 Elsevier B.V. All rights reserved.
We propose a multimodal free-form registration algorithm based on maximization of mutual information. the warped image is modeled as a viscous fluid that deforms under the influence of forces derived from the gradient...
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We propose a multimodal free-form registration algorithm based on maximization of mutual information. the warped image is modeled as a viscous fluid that deforms under the influence of forces derived from the gradient of the mutual information registration criterion. Parzen windowing is used to estimate the joint intensity probability of the images to be matched. the method is evaluated for non-rigid inter-subject registration of MR brain images. the accuracy of the method is verified using simulated multi-modal MR images with known ground truth deformation. the results show that the root mean square difference between the recovered and the ground truth deformation is smaller than 1 voxel. We illustrate the application of the method for atlas-based brain tissue segmentation in MR images in case of gross morphological differences between atlas and patient images. (C) 2003 Elsevier B.V. All rights reserved.
In this paper we present a new algorithm for 3D medicalimage segmentation. the algorithm is fast, relatively simple to implement, and semi-automatic. It is based on minimizing a global energy defined from a learned n...
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ISBN:
(数字)9783540399032
ISBN:
(纸本)3540204644
In this paper we present a new algorithm for 3D medicalimage segmentation. the algorithm is fast, relatively simple to implement, and semi-automatic. It is based on minimizing a global energy defined from a learned non-parametric estimation of the statistics of the region to be segmented. Implementation details are discussed and source code is freely available as part of the 3D Slicer project. In addition, a new unified set of validation metrics is proposed. Results on artificial and real MRI images show that the algorithm performs well on large brain structures both in terms of accuracy and robustness to noise.
We propose a method for automatically correcting the spherical topology of any segmentation under any digital connectivity. A multiple region growing process, concurrently acting on the foreground and the background, ...
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ISBN:
(数字)9783540399032
ISBN:
(纸本)3540204644
We propose a method for automatically correcting the spherical topology of any segmentation under any digital connectivity. A multiple region growing process, concurrently acting on the foreground and the background, divides the segmentation into connected components and successive minimum cost decisions guarantee convergence to correct spherical topology. In contrast to existing procedures that suppose specific initial segmentation (full connectivity, no cavities...) and are designed for a particular task (cortical representation), no assumption is made on the initial image. Our method applied to subcortical segmentations allows us to correct the topology of fourteen non-cortical structures in less than a minute.
Finding point correspondence in anatomical images is a key step in shape analysis and deformable registration. this paper proposes an automatic correspondence detection algorithm using wavelet-based attribute vectors ...
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ISBN:
(数字)9783540399032
ISBN:
(纸本)3540204644
Finding point correspondence in anatomical images is a key step in shape analysis and deformable registration. this paper proposes an automatic correspondence detection algorithm using wavelet-based attribute vectors defined on every image voxel. the attribute vector reflects the anatomical characteristics in a large neighborhood around the respective voxel. It plays the role of a morphological signature for each voxel and is therefore made as distinctive as possible. Correspondence is then determined via similarity of attribute vectors. Experiments with brain MR images show that the algorithm performs at least as well as human experts, even for complex cortical structures.
this paper presents a high-quality glass-less autostereoscopic display system that is integrated into image-guided surgery. the glass-less autostereoscopic image was created by employing a modification of Integral Vid...
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ISBN:
(数字)9783540399032
ISBN:
(纸本)3540204644
this paper presents a high-quality glass-less autostereoscopic display system that is integrated into image-guided surgery. the glass-less autostereoscopic image was created by employing a modification of Integral Videography (IV), which is an animated extension of Integral Photography. IV records and reproduces 3-D images using a micro convex lens array and plat display, which can display geometrically accurate 3-D autostereoscopic images and reproduce motion parallax without any need for special viewing devices. this paper reports the use of high-resolution IV display and high performance computing for producing medical 3-D image. We evaluate the feasibility of this display by using a set of medicalimage with segmentation and reproducing 3-D CT and MRI autostereoscopic image for surgical planning and intra-operative guidance. the main contribution of this paper is application and modification of medical 3-D display technique originally developed in high-resolution autostereoscopic display and high performance computing.
A similarity measure for nonrigid volume registration with known joint distribution of a targeted tissue is developed to process tissue slide at the boundaries between the targeted and non-targeted tissues. Pre-segmen...
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A similarity measure for nonrigid volume registration with known joint distribution of a targeted tissue is developed to process tissue slide at the boundaries between the targeted and non-targeted tissues. Pre-segmentation of the targeted tissue is unnecessary. this measure is applied to registering volumes acquired at different time-phases in dynamic CT scans of the liver using contrast materials and can be derived for the case where only the joint distribution of the targeted tissue is known. the similarity measure is formulated as a likelihood by introducing a concept termed 'exclusivity condition' and embedded into a cost function for nonrigid registration to be combined withthe smoothness term. In addition, a practical method for estimating the joint distribution of the liver from unregistered clinical CT data is described. We demonstrate experimentally that tissue slide is effectively processed by this proposed measure using simulated dynamic CT data generated from a software phantom and clinical CT data of eight patients. (C) 2003 Elsevier B.V. All rights reserved.
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