An ultra-fast user-steered image segmentation paradigm: live wire on the fly

Falcão, Alexandre X.; Udupa, Jayaram K.; Miyazawa, Flávio Keidi

doi:10.1109/42.832960

Cited by 248 publications

(188 citation statements)

References 25 publications

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“…By taking the absolute values of the inner products, the algorithm ignores the actual directions of the eigenvectors and considers only their orientations. Optimal paths based on this cost function are computed by a version of Dijkstra's shortest-path algorithm (30) based on a discretization of the cost values and the use of a circular priority queue (19,20,22). The placing of starting points is facilitated by applying "local snapping," which implies that the cursor is always moved to the locally lowest cost point in a small window, of size w ϫ w pixels, around the actual cursor position.…”

Section: Literature Citedmentioning

confidence: 99%

Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images

et al. 2004

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Background: For the investigation of the molecular mechanisms involved in neurite outgrowth and differentiation, accurate and reproducible segmentation and quantification of neuronal processes are a prerequisite. To facilitate this task, we developed a semiautomatic neurite tracing technique. This article describes the design and validation of the technique. Methods:The technique was compared to fully manual delineation. Four observers repeatedly traced selected neurites in 20 fluorescence microscopy images of cells in culture, using both methods. Accuracy and reproducibility were determined by comparing the tracings to highresolution reference tracings, using two error measures. Labor intensiveness was measured in numbers of mouse clicks required. The significance of the results was determined by a Student t-test and by analysis of variance. Results: Both methods slightly underestimated the true neurite length, but the differences were not unanimously

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Section: Literature Citedmentioning

confidence: 99%

Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images

et al. 2004

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“…If Trial points are ordered in a min-heap data structure, the computational complexity of the FMM is O(N log N), where N is the total number of grid points. Some authors [11,13,21] have proposed various versions of the fast marching in order to get an O(N ) complexity. These approaches are less accurate on the result or assuming some hypotheses that are not met in our method.…”

Section: Ordered Sweeping Of Grid Pointsmentioning

confidence: 99%

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

Benmansour

Cohen

2008

J Math Imaging Vis

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In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.

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“…For example, our current implementation uses a heap data structure to manage the sorted queue when computing the IFT, but . To obtain a tunnel-free surface, all live-wire curves generated between the two user-defined curves are connected to their adjacent curves by triangular polygons according to [4] better performance can be achieved by using a circular queue structure instead.…”

Section: Performancementioning

confidence: 99%

“…Live-wire [1,4] is a popular semi-automatic segmentation method that has been used successfully for many 2D problems. Various ways of extending this method to segment volume images have been proposed in the literature.…”

Section: Introductionmentioning

confidence: 99%

A 3D Live-Wire Segmentation Method for Volume Images Using Haptic Interaction

Malmberg

Vidholm

Nyström

2006

Discrete Geometry for Computer Imagery

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Abstract. Designing interactive segmentation methods for digital volume images is difficult, mainly because efficient 3D interaction is much harder to achieve than interaction with 2D images. To overcome this issue, we use a system that combines stereo graphics and haptics to facilitate efficient 3D interaction. We propose a new method, based on the 2D live-wire method, for segmenting volume images. Our method consists of two parts: an interface for drawing 3D live-wire curves onto the boundary of an object in a volume image, and an algorithm for connecting two such curves to create a discrete surface.

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An ultra-fast user-steered image segmentation paradigm: live wire on the fly

Cited by 248 publications

References 25 publications

Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images

Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

A 3D Live-Wire Segmentation Method for Volume Images Using Haptic Interaction

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