Efficient numerical schemes for Chan-Vese active contour models in image segmentation

Liang, Jiuzhen; Li, Min; Liao, Cuicui

doi:10.1007/s11042-017-5232-6

Cited by 3 publications

(3 citation statements)

References 28 publications

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“…As the mitigation technique of the models' power functional, a variety of variational methods have been developed. They are mostly dependent on using an optimization algorithm to overcome the related Euler Lagrange simultaneous equations [25]. These techniques are ideal for removing noise & other undesirable tiny scale features while keeping edges intact.…”

Section: Methodsmentioning

confidence: 99%

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Biomedical image restoration using machine learning GPU acceleration approach for precision improvement

Hazela

Aarti

Khandelwal

et al. 2022

ijhs

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Focusing the image in a single x-ray projection, an algorithm proposed for actual time volumetric image rebuilt and 3-dimensional location of the lump. Using the Principal Component Analysis (PCA) initialize the parameterized Deformation Vector Fields (DVF) of pulmonary movement. By adjusting the PCA coefficients, applied the DVF applied to optimize the reference image so that, the simulated projection of the rebuilt image matches the observed projection. The digital phantom & patient information was used to evaluate the technique. The phantom has an average relative image rebuilt error of 7.5 percent and a 3-dimensional location of the lump inaccuracy of 0.9 mm, correspondingly. The patient's location of the lump inaccuracy is less than 2 mm. On a GPU NVIDIA C1060, recreating a single volumetric image from every projection takes about 0.2 & 0.3 secs for patient and phantom. From a single image, clinical relevance could lead to reliable 3-dimensional lump tracking.

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Section: Methodsmentioning

confidence: 99%

“…DIR between the finish to expiration phase and most other stages, using the finish to expiration stage as the reference image. The DIR method is a GPU-based quick demonic method [25]. The 9 DVF from DIR were then Principal Component Analysis, with 3 PCA correlations and support vectors maintained in this method.…”

Section: Proposed Workmentioning

confidence: 99%

Biomedical image restoration using machine learning GPU acceleration approach for precision improvement

Hazela

Aarti

Khandelwal

et al. 2022

ijhs

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show abstract

“…23 In recent years, many novel efficient and improved methods have applied to solve the level set evolution equations. Liang et al 24 constructed a numerical solution method for multiple Lagrangian variational integrators of the CV model, which has achieved better segmentation results. Wei et al 25 gave a normal vector projection method for the CV model and obtained a global optimal solution.…”

mentioning

confidence: 99%

A sweeping optimization algorithm for the global cosine fitting energy image segmentation model

Zou

Chen

et al. 2021

Concurrency and Computation

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Image segmentation plays a pivotal role in image processing. Level set model is a traditional variation image segmentation method. In order to achieve level set evolution equation, the level set energy functionals are minimized with the gradient descent methods and then the partial differential equation (PDE) was solved by finite difference scheme. Slow speed is one of its disadvantages. We propose a sweep optimization algorithm based on global cosine fitting (GCF) energy. Instead of calculating the PDE and the curvature, the proposed sweeping algorithm directly calculates the energy change when a pixel moves from one side of evolving contour to the other. It checks whether the GCF energy is decreased or not. The proposed algorithm has many advantages. For example, independent of initial level set contour positions and parameters, need not consider the Courant Friedrichs Lew condition and the regularization energy term. The proposed algorithm can be easily extended to high dimension image segmentation. The experiments on synthetic images, noise images and real images demonstrate the effectiveness of the proposed sweeping optimization algorithm.

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Crack identification method of highway tunnel based on image processing

Yin

Gao

et al. 2023

Journal of Traffic and Transportation Engineering (English Edit

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Efficient numerical schemes for Chan-Vese active contour models in image segmentation

Cited by 3 publications

References 28 publications

Biomedical image restoration using machine learning GPU acceleration approach for precision improvement

Biomedical image restoration using machine learning GPU acceleration approach for precision improvement

A sweeping optimization algorithm for the global cosine fitting energy image segmentation model

Crack identification method of highway tunnel based on image processing

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