Results 1  10
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11
Edge Detection and Ridge Detection with Automatic Scale Selection
 CVPR'96
, 1996
"... When extracting features from image data, the type of information that can be extracted may be strongly dependent on the scales at which the feature detectors are applied. This article presents a systematic methodology for addressing this problem. A mechanism is presented for automatic selection of ..."
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Cited by 267 (21 self)
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When extracting features from image data, the type of information that can be extracted may be strongly dependent on the scales at which the feature detectors are applied. This article presents a systematic methodology for addressing this problem. A mechanism is presented for automatic selection of scale levels when detecting onedimensional features, such as edges and ridges. Anovel concept of a scalespace edge is introduced, defined as a connected set of points in scalespace at which: (i) the gradient magnitude assumes a local maximum in the gradient direction, and (ii) a normalized measure of the strength of the edge response is locally maximal over scales. An important property of this definition is that it allows the scale levels to vary along the edge. Two specific measures of edge strength are analysed in detail. It is shown that by expressing these in terms of &gamma;normalized derivatives, an immediate consequence of this definition is that fine scales are selected for sharp edges (so as to reduce the shape distortions due to scalespace smoothing), whereas coarse scales are selected for diffuse edges, such that an edge model constitutes a valid abstraction of the intensity profile across the edge. With slight modifications, this idea can be used for formulating a ridge detector with automatic scale selection, having the characteristic property that the selected scales on a scalespace ridge instead reflect the width of the ridge.
A Review of Vessel Extraction Techniques and Algorithms
 ACM Computing Surveys
, 2000
"... Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by means of a classification of the existing r ..."
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Cited by 128 (0 self)
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Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by means of a classification of the existing research. While we have mainly targeted the extraction of blood vessels, neurosvascular structure in particular, we have also reviewed some of the segmentation methods for the tubular objects that show similar characteristics to vessels. We have divided vessel segmentation algorithms and techniques into six main categories: (1) pattern recognition techniques, (2) modelbased approaches, (3) trackingbased approaches, (4) artificial intelligencebased approaches, (5) neural networkbased approaches, and (6) miscellaneous tubelike object detection approaches. Some of these categories are further divided into sub categories. We have also created tables to compare the papers in each category against such criteria as dimensionality, input type, preprocessing, user interaction, and result type.
Shape Analysis of Brain Structures Using Physical and Experimental Modes
 In CVPR94. IEEE Computer Society
, 1994
"... This paper presents a framework for analyzing the shape deformation of structures within the human brain. A mathematical model is developed describing ..."
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Cited by 32 (9 self)
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This paper presents a framework for analyzing the shape deformation of structures within the human brain. A mathematical model is developed describing
From 2d images to 3d face geometry
 In Proceedings of the 2nd International Conference on Automated Face and Gesture Recognition (FG'96
, 1996
"... This paper presents a global scheme for 3D face reconstruction and face segmentation into a limited number of analytical patches from stereo images. From a depth map, we generate a 3D model of the face which is iteratively deformed under stereo and shapefromshading constraints as well as different ..."
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Cited by 10 (1 self)
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This paper presents a global scheme for 3D face reconstruction and face segmentation into a limited number of analytical patches from stereo images. From a depth map, we generate a 3D model of the face which is iteratively deformed under stereo and shapefromshading constraints as well as differential features. This model enables us to improve the quality of the depth map, from which we perform the segmentation and the approximation of the surface. 1
Segmentation by Adaptive Geodesic Active Contours
 IN: MICCAI
, 2000
"... This paper introduces the use of spatially adaptive components into the geodesic active contour segmentation method for application to volumetric medical images. These components are derived from local structure descriptors and are used both in regularization of the segmentation and in stabilizati ..."
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Cited by 9 (1 self)
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This paper introduces the use of spatially adaptive components into the geodesic active contour segmentation method for application to volumetric medical images. These components are derived from local structure descriptors and are used both in regularization of the segmentation and in stabilization of the imagebased vector field which attracts the contours to anatomical structures in the images. Theyare further used to incorporate prior knowledge about spatial location of the structures of interest. These components can potentially decrease the sensitivity to parameter settings inside the contour evolution system while increasing robustness to image noise. We show segmentation results on blood vessels in magnetic resonance angiography data and bone in computed tomography data.
Extraction of 3D anatomical point landmarks based on invariance principles. Pattern Recognition
, 1999
"... We describe 3D operators for extracting anatomical landmarks which are based on only firstorder partial derivatives of an image. To improve the predictability of the extraction results we analyze certain properties of the operators. First, we provide a statistical interpretation in terms of the Cra ..."
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Cited by 9 (2 self)
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We describe 3D operators for extracting anatomical landmarks which are based on only firstorder partial derivatives of an image. To improve the predictability of the extraction results we analyze certain properties of the operators. First, we provide a statistical interpretation in terms of the Cramér—Rao bound representing the minimal localization uncertainty. Second, we show that the operators can be derived on the basis of invariance principles. It turns out that the operators form a complete set of principal invariants. Third, we analyze the detection performance using a certain type of performance visualization and a scalar performance measure. Experimental results are presented for 3D tomographic
On Computing Structural Changes in Evolving Surfaces and their Appearance
 International Journal of Computer Vision
, 2001
"... As a surface undergoes a oneparameter family of deformations, its shape and its appearance change smoothly except at certain critical parameter values where abrupt structural changes occur. This paper considers the case of surfaces defined as the zero set of smooth density functions undergoing a Ga ..."
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Cited by 2 (0 self)
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As a surface undergoes a oneparameter family of deformations, its shape and its appearance change smoothly except at certain critical parameter values where abrupt structural changes occur. This paper considers the case of surfaces defined as the zero set of smooth density functions undergoing a Gaussian diffusion process and addresses the problem of computing the critical parameter values corresponding to structural changes in the parabolic curves of a surface and in its aspect graph. An algorithm based on homotopy continuation and curve tracing is proposed in the case of polynomial density functions, whose zero set is an algebraic surface. It has been implemented and examples are presented.
Incorporating Differential Constraints in a 3D Reconstruction Process Application to
"... Stereo We propose to incorporate a priori geometric constraints in a 3–D stereo reconstruction scheme to cope with the many cases where image information alone is not sufficient to accurately recover 3–D shape. Our approach is based on the iterative deformation of a 3–D surface mesh to minimize an o ..."
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Stereo We propose to incorporate a priori geometric constraints in a 3–D stereo reconstruction scheme to cope with the many cases where image information alone is not sufficient to accurately recover 3–D shape. Our approach is based on the iterative deformation of a 3–D surface mesh to minimize an objective function. We show that combining anisotropic meshing with a nonquadratic approach to regularization enables us to obtain satisfactory reconstruction results using triangulations with few vertices. Structural or numerical constraints can then be added locally to the reconstruction process through a constrained optimization scheme. They improve the reconstruction results and enforce their consistency with a priori knowledge about object shape. The strong description and modeling properties of differential features make them useful tools that can be efficiently used as constraints for 3–D reconstruction. 1.
Extraction of Thin Nets in greylevel images  Application: Roads and Blood Vessels
"... In this paper, we describe a new approach for extracting thin nets in 2D grey level images. The key point is to model thin nets as the crest lines of the image surface. Crest lines are the lines where one of the two principal curvatures is locally extremal. We define these lines using first, second ..."
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In this paper, we describe a new approach for extracting thin nets in 2D grey level images. The key point is to model thin nets as the crest lines of the image surface. Crest lines are the lines where one of the two principal curvatures is locally extremal. We define these lines using first, second and third derivatives of the image. We compute the image derivatives using recursive filters approximating the Gaussian filter and its derivatives. This paper presents an algorithm to extract thin nets from 2D images and we apply this method to the extraction of roads in satellite images and blood vessels in medical images.
The SpaceTime Map Applied to Drosophila Embryogenesis
, 1998
"... Many physical phenomena have complex structure in both space and time. To systematically understand these phenomena from images we need representations that unify the treatment of space and time. We create such a representation, the spacetime map, for characterizing contour evolutions. Many types o ..."
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Many physical phenomena have complex structure in both space and time. To systematically understand these phenomena from images we need representations that unify the treatment of space and time. We create such a representation, the spacetime map, for characterizing contour evolutions. Many types of information are computed and stored as facets of the map, registered to a spacetime manifold generated by the evolution. We demonstrate our representation on the example of Drosophila embryogenesis in optical section. Changes in embryo shape are reflected as changes in the dye distribution along the deforming vitelline membrane contour. We extract a series of contours and create a twodimensional spacetime map. We track intensity on this map to obtain a velocity field. We extract spacetime ridges and significant motions on this map, and use them along with prior knowledge to recognize the significant features and events of embryogenesis. 1.