Segmentation of external force field for automatic initialization and splitting of snakes

Li, Chunming; Liu, Jundong; Fox, M.D.

doi:10.1016/j.patcog.2004.12.015

Cited by 94 publications

(45 citation statements)

References 19 publications

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“…Some variations of these ideas are the multi-directional GGVF [57] and the nonlinear diffusion model [58]. Recent modifications are the convolution vector flow [59], Poisson gradient vector field [60,61], segmented external force field [62], dynamic directional gradient vector flow [63], normal gradient vector field [64], priory directional information vector flow [65], adaptive diffusion flow [66], multi-feature gradient vector flow [67] and divergence gradient vector flow [68]. A competing approach called the level set method (LSM) [69] is based on the ideas proposed by Osher and Sethian [70] to use a model of propagating liquid interfaces with curvature-dependent speeds.…”

Section: Introductionmentioning

confidence: 99%

“…However, the LSM makes it difficult to impose arbitrary geometric or topological constraints on the evolving contour via the higher-dimensional hypersurface. Besides, the level set models may generate shapes having inconsistent topology with respect to the actual object, when applied to noisy images characterized by large boundary gaps [75] and nonclosed curves [62]. Besides, the LSM is computationally expensive since it requires to propagate a 2D object (the level set surface) in the 3D space, whereas the active contour methods evolve a 1D object (the closed contour) in the 2D space.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, [62] segments the external force field, to divide the image domain into disjoint regions. The snakes can be individually initialized within each of the enclosures and moved to the targeted object boundary within it, avoiding being attracted by other objects.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Phase portrait analysis for automatic initialization of multiple snakes for segmentation of the ultrasound images of breast cancer

Kirimasthong

Rodtook

Chaumrattanakul

et al. 2016

Pattern Anal Applic

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Segmentation of ultrasound (US) images of breast cancer is one of the most challenging problems of modern medical image processing. A number of popular codes for US segmentation are based on the active contours (snakes) and on a variety of modifications of gradient vector flow. The snakes have been used to locate objects in various applications of medical images. However, the main difficulty in applying the method is initialization. Therefore, we suggest a new method for automatic initialization of active contours based on phase portrait analysis (PPA) of the underlying vector field and a sequential initialization of trial multiple snakes. The PPA makes it possible to exclude the noise and artifacts and properly initialize the multiple snakes. In turn, the trial snakes allow us to differentiate between the seeds initialized inside and outside the desired object. While preceding methods require the manual selection of at least one seed point inside the object or rely on the particular distribution of the gray levels, the proposed method is fully automatic and robust to the noise, as can be seen from the tests with synthetic and real images.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Phase portrait analysis for automatic initialization of multiple snakes for segmentation of the ultrasound images of breast cancer

Kirimasthong

Rodtook

Chaumrattanakul

et al. 2016

Pattern Anal Applic

View full text Add to dashboard Cite

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“…Edge-based models [1][2][3][4][5] find contours by minimizing the edgy function which depends on its shape and location within the image. The energy function is composed of a weighted combination of internal and external forces and stopping term.…”

Section: Introductionmentioning

confidence: 99%

The Estimation of Parameters to minimize the Energy Function of the Piecewise Constant Model Using Three-way Analysis of Variance

Joo¹,

Cho²,

Seo³

2012

The Journal of Korea Navigation Institute

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The result of imaging segmentation becomes different with the parameters involved in the segmentation algorithms; therefore, the parameters for the optimal segmentation have been found through a try and error.In this paper, we propose the method to find the best values of parameters involved in the area-based active contour method using three-way ANOVA. The segmentation result applied by three-way ANOVA is compared with the optimal segmentation which is drawn by user. We use the global consistency rate for comparing two segmentations. Finally, we estimate the main effects and interactions between each parameter using three-way ANOVA, and then calculate the point and interval estimate to find the best values of three parameters. The proposed method will be a great help to find the optimal parameters before working the motion segmentation using piecewise constant model.

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“…However, the level set representation makes it difficult to impose arbitrary geometric or topological constraints on the evolving contour via the higher dimensional hyper surface [15]. Besides, the level set models may generate shapes having inconsistent topology with respect to the actual object, when applied to noisy images characterized by large boundary gaps [33] requiring exhaustive optimization to accomplish reasonable run times [34].…”

Section: Introductionmentioning

confidence: 99%

Phase Portrait Analysis for Multiresolution Generalized Gradient Vector Flow

Chucherd

Rodtook

Makhanov

2010

IEICE Trans. Inf. & Syst.

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SUMMARYWe propose a modification of the generalized gradient vector flow field techniques based on multiresolution analysis and phase portrait techniques. The original image is subjected to mutliresolutional analysis to create a sequence of approximation and detail images. The approximations are converted into an edge map and subsequently into a gradient field subjected to the generalized gradient vector flow transformation. The procedure removes noise and extends large gradients. At every iteration the algorithm obtains a new, improved vector field being filtered using the phase portrait analysis. The phase portrait is applied to a window with a variable size to find possible boundary points and the noise. As opposed to previous phase portrait techniques based on binary rules our method generates a continuous adjustable score. The score is a function of the eigenvalues of the corresponding linearized system of ordinary differential equations. The salient feature of the method is continuity: when the score is high it is likely to be the noisy part of the image, but when the score is low it is likely to be the boundary of the object. The score is used by a filter applied to the original image. In the neighbourhood of the points with a high score the gray level is smoothed whereas at the boundary points the gray level is increased. Next, a new gradient field is generated and the result is incorporated into the iterative gradient vector flow iterations. This approach combined with multiresolutional analysis leads to robust segmentations with an impressive improvement of the accuracy. Our numerical experiments with synthetic and real medical ultrasound images show that the proposed technique outperforms the conventional gradient vector flow method even when the filters and the multiresolution are applied in the same fashion. Finally, we show that the proposed algorithm allows the initial contour to be much farther from the actual boundary than possible with the conventional methods. key words: phase portrait analysis, multiresolution analysis, medical image processing

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Segmentation of external force field for automatic initialization and splitting of snakes

Cited by 94 publications

References 19 publications

Phase portrait analysis for automatic initialization of multiple snakes for segmentation of the ultrasound images of breast cancer

Phase portrait analysis for automatic initialization of multiple snakes for segmentation of the ultrasound images of breast cancer

The Estimation of Parameters to minimize the Energy Function of the Piecewise Constant Model Using Three-way Analysis of Variance

Phase Portrait Analysis for Multiresolution Generalized Gradient Vector Flow

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