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This paper proposes an entropy-weighted local intensity clustering-based model for segmenting intensity inhomogeneous images caused by the bias field. The variational model minimizes an energy functional consisting of a regularization term of the ...

The level set method is a classical method to solve the Chan-Vese model for the binary image segmentation problem. Some efficient methods such as the convex relaxed methods and the steep descent methods based on a suitable constraint have been ...

Image-based rock typing is carried out to classify an image of the heterogeneous rock sample into different rock types where each rock type can be treated as a homogeneous porous medium. In this study, we propose an innovative method ...

• LHF is used to increase the structure contrast between different rock types.
• ...

Chan-Vese (CV) model promotes the evolution of level set curve based on the gray distribution inside and outside the curve. It has a better segmentation effect on images with intensity homogeneity and obvious contrast. However, when the gray ...

Magnetic resonance image (MRI) can detect a variety of conditions of the spine, including problems with the bones, soft tissues, and disks. Accurate localization and segmentation of intervertebral disc is crucial for the assessment of spine disease ...

Medical image segmentation is a hot topic in the field medical image processing. The segmentation methods based on level set and the ones based on fuzzy set are currently very popular in the field of medical image segmentation. But these methods do not ...

An image segmentation algorithm based on the ramp width reduction combined with an Intersecting Cortical Model (ICM) is proposed against problems that ICM in the segmentation of image with weak edge produces geometric distortion. By virtue of prewitt ...

The new structure is designed to transform a CT scan image into neutrosophic domain which approximately extracts the liver image structure.A new algorithm is introduced to identify the initial contour within liver image. This initial contour extends ...

Image processing of medical images gives opportunities to researchers, because what is accurate segmentation that is still challenging and accurate segmentation is required for better analysis of images. Energy based methods like level set and active ...

In this paper, we propose a novel hybrid edge and region based active contour in a variational level set formulation without reinitialization for image segmentation. The proposed model associate a penalizing term that penalizes the deviation of the ...

Segmentation is one of the fundamental tasks in computer vision applications. For natural images there exist a vast amount of sophisticated segmentation methods in the literature. However, these standard methods tend to fail in the presence of non-...

In this paper, we propose an active contour model and its corresponding algorithms with detailed implementation for image segmentation. In the proposed model, the local and global region fitting energies are described by the combination of the local and ...

A novel algorithm is proposed for the segmentation of the lumen and bifurcation boundaries of the carotid artery in B-mode ultrasound images. It uses the image contrast characteristics of the lumen and bifurcation of the carotid artery in relation to ...

In this paper, we propose a competitive learning based Chan-Vese model (CLCV) for two-phase image segmentation by coupling the Chan-Vese model and the rival penalized competitive learning mechanism from the point of view of the cost function for the ...

In this paper, we propose an improved Chan-Vese (CV) model that uses Kullback-Leibler (KL) distances and local neighborhood information (LNI). Due to the effects of heterogeneity and complex constructions, the performance of level set segmentation is ...

Chan-Vese (CV) model is a promising active contour model for image segmentation. However, CV model does not utilize local region information of images and thus CV model based segmentation methods cannot achieve good segmentation results for complex ...

The graph cut framework presents an efficient method for approximating the minimum of the popular Chan-Vese functional for image segmentation. However, a fundamental drawback of graph cuts is a need for a dense neighbourhood system in order to avoid ...

In this article, we propose a novel model to overcome the drawbacks of the modified Chan–Vese (MCV) model. Our model is devoted to find an optimal partition of inhomogeneous regions accurately and computationally efficient. MCV model was proposed on the ...

The active contours without edges model of Chan and Vese (IEEE Transactions on Image Processing 10(2):266---277, 2001) is a popular method for computing the segmentation of an image into two phases, based on the piecewise constant Mumford-Shah model. ...

Image segmentation is a classical and crucial problem in the fields of computer vision and image understanding. Since Kass et al. proposed the seminal model, i.e. snake, active contour model has rapid development and becomes a research hotspot. It ...