this paper introduces a new technique to detect the coronary arteries as well as other heart's peripheral vessels. After finding the location of the myocardium through a graph theoretic segmentation method, the al...
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ISBN:
(纸本)3540229760
this paper introduces a new technique to detect the coronary arteries as well as other heart's peripheral vessels. After finding the location of the myocardium through a graph theoretic segmentation method, the algorithm models the heart with a biaxial ellipsoid. For each point of this ellipsoid, we compute the collection of intensities that are normal to the surface. this collection is then filtered to detect the cardiovascular structures. Ultimately, the vessels centerline points are detected using a vessel tracking algorithm, and linked together to form a complete coronary artery tree.
A method fully utilizing multiscale line filter responses is presented to estimate the point spread function (PSF) of a CT scanner and diameters of small tubular structures based on the PSF. the estimation problem is ...
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ISBN:
(纸本)3540229760
A method fully utilizing multiscale line filter responses is presented to estimate the point spread function (PSF) of a CT scanner and diameters of small tubular structures based on the PSF. the estimation problem is formulated as a least square fitting of a sequence of multiscale responses obtained at each medial axis point to the precomputed multiscale response curve for the ideal line model. the method was validated through phantom experiments and demonstrated to accurately measure small-diameter structures which are significantly overestimated by conventional methods based on the full width half maximum (FWHM) and zero-crossing edge detection.
A new 3D segmentation method based on the level set technique is proposed. the main contribution is a robust evolutionary model which requires no fine tuning of parameters. A closed 3D surface propagates from an initi...
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ISBN:
(纸本)3540229760
A new 3D segmentation method based on the level set technique is proposed. the main contribution is a robust evolutionary model which requires no fine tuning of parameters. A closed 3D surface propagates from an initial position towards the desired region boundaries through an iterative evolution of a specific 4D implicit function. Information about the regions is involved by estimating, at each iteration, parameters of probability density functions. the method can be applied to different kinds of data, e.g for segmenting anatomical structures in 3D magnetic resonance images and angiography. Experimental results of these two types of data are discussed.
Non-rigid registration of multimodal images is a challenging problem. One approach, maximization of mutual information, has been shown to be effective for registering certain image modalities and is currently consider...
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ISBN:
(纸本)3540229760
Non-rigid registration of multimodal images is a challenging problem. One approach, maximization of mutual information, has been shown to be effective for registering certain image modalities and is currently considered the standard against which all other techniques are measured. In this paper, we propose an alternative representation of an image based on local phases rather than intensities;we then show how mutual information can be extended to this representation. Local phase acts as a description of local image structure, enabling mutual phase information to detect complex image relationships that are hard or impossible to detect using mutual intensity information. Typical results are presented, comparing the performance of phase and intensity mutual information methods on simulated MR and ultrasound images.
A new segmentation scheme is proposed for 3D vascular tree delineation in CTA data sets, which has two essential features. First, the segmentation is carried out locally in a small volume of interest (VOI), second, a ...
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ISBN:
(纸本)3540229760
A new segmentation scheme is proposed for 3D vascular tree delineation in CTA data sets, which has two essential features. First, the segmentation is carried out locally in a small volume of interest (VOI), second, a global topology estimation is made to initialize a new VOI. the use of local Vol allows that parameter settings for the level set speed function can be optimally set depending on the local image content, which is advantageous especially in vascular tree segmentation where contrast may change significantly, especially in the distal part of the vascular. Moreover, a local approach is significantly faster. A comparison study on five CTA data sets showed that our method has the potential to segment larger part of the vessel tree compared to a similar global level set based segmentation, and in substantially less computation time.
this paper reports the performance evaluation of a method for visualisation and quantification of intraoperative cortical surface deformations. this method consists in the acquisition of 3D surface meshes of the opera...
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ISBN:
(纸本)3540229779
this paper reports the performance evaluation of a method for visualisation and quantification of intraoperative cortical surface deformations. this method consists in the acquisition of 3D surface meshes of the operative field directly in the neuronavigator's coordinate system by means of stereoscopic reconstructions, using two cameras attached to the microscope oculars. the locations of about 300 surfaces are compared to the locations of two reference surfaces from a physical phantom: a segmented CT scan withimage-to-physical fiducial-based registration, used to compute the overall system performance, and a cloud of points acquired withthe neuronavigator's optical localiser, used to compute the intrinsic error of our method. the intrinsic accuracy of our method was shown to be within 1 mm.
Regional myocardial motion analysis is used in clinical routine to inspect cardiac contraction in myocardial diseases such as infarction or hypertrophy. Physicians/radiologists can recognize abnormal cardiac motion be...
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ISBN:
(纸本)3540229760
Regional myocardial motion analysis is used in clinical routine to inspect cardiac contraction in myocardial diseases such as infarction or hypertrophy. Physicians/radiologists can recognize abnormal cardiac motion because they have knowledge about normal heart contraction. this paper explores the potential of Independent Component Analysis (ICA) to extract local myocardial contractility patterns and to use them for the automatic detection of regional abnormalities. A qualitative evaluation was performed using 42 healthy volunteers to train the ICA model and 6 infarct patients to test the detection and localization. this experiment shows that the evaluation results correlate very well to the clinical gold standard: delayed-enhancement MR images.
Currently, minimally invasive cardiac surgery (MICS) faces several limitations, including inadequate training methods using non-realistic models, insufficient surgery planning using 2D images, and the lack of global, ...
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ISBN:
(纸本)3540229760
Currently, minimally invasive cardiac surgery (MICS) faces several limitations, including inadequate training methods using non-realistic models, insufficient surgery planning using 2D images, and the lack of global, 3D guidance during the procedure. To address these issues we are developing the Virtual Cardiac Surgery Platform (VCSP) - a virtual reality model of the patient specific thorax, derived from pre-procedural images. Here we present an image registration-based method for customizing a geometrical template model of the heart to any given patient, and validate it using manual segmentation as the gold standard. On average, the process is accurate to within 3.3 +/- 0.3 mm in MR images, and 2.4 +/- 0.3 min in CT images. these results include inaccuracies in the gold standard, which are on average 1.6 +/- 0.2 and 0.9 +/- 0.2 mm for MR and CT images respectively. We believe this method adequately prepares templates for use within VCSP, prior to and during MICS.
this paper presents a curve evolution model for 3D slice-by-slice image segmentation and its application in medical imaging. It is an iterative process based on the dual front evolution and the morphological dilatatio...
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ISBN:
(纸本)3540229760
this paper presents a curve evolution model for 3D slice-by-slice image segmentation and its application in medical imaging. It is an iterative process based on the dual front evolution and the morphological dilatation to iteratively deform the initial contour towards the segmentation result. the dual front evolution model is proposed to form the new boundary by the contact position of two (or more) curves evolving in opposite directions. the fast sweeping evolution scheme is introduced for the contour evolution and the velocities for the propagation of the different curves are defined in accordance withthe region-based characteristics. this model can achieve the global energy minimum and solves the disadvantages of classical level set evolution methods. Experimental results are given to illustrate the robustness of the method and its performance in precise region boundary localization and medical imaging.
this paper presents an approach for deformable registration of a normal brain atlas to visible anatomic structures in a tumor-diseased brain image. We restrict our attention to cortical surfaces. First, a model surfac...
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ISBN:
(纸本)3540229760
this paper presents an approach for deformable registration of a normal brain atlas to visible anatomic structures in a tumor-diseased brain image. We restrict our attention to cortical surfaces. First, a model surface in the atlas is warped to the tumor-diseased brain image via a HAMMER-based volumetric registration algorithm. However, the volumetric warping is generally inaccurate around the tumor region, due to the lack of reliable features to which the atlas can be matched. therefore, the model structures for which no reliable matches are found are labeled by a Markov Random Field-Maximum A Posteriori approach. A statistically-based interpolation method is then used to correct/refine the volumetric warping for those structures. Finally, withthe good initialization obtained by the above steps and the identification of the part of the model anatomy that can be recognized in the patient's image, the model surface is adaptively warped to its counterpart that is visible in the tumor-diseased brain imagethrough a surface registration procedure. Preliminary results show good performance on both simulated and real tumor-diseased brain images.
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