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 …

Image segmentation plays an important role in many medical imaging systems, yet in
complex circumstances it remains an open problem. One of the main difficulties is the …

Medical image segmentation is a very challenging task, not only because the intensity of the
medical image itself is not uniform, but also it may be accompanied by the impact of noise …

The level set method is widely used in medical image segmentation, in which the
performance is seriously subject to the initialization and parameters configuration. An …

This paper presents a novel correntropy-based level set method (CLSM) for medical image
segmentation and bias field correction. Firstly, we build a local bias-field-corrected fitting …

Level set based methods are being increasingly used in image segmentation. In these
methods, various shape constraints can be incorporated into the energy functionals to obtain …

It is usually difficult to correctly segment medical images with intensity inhomogeneity, which
is of great significance in understanding of medical images. The local image intensity …

In this paper, a level set model without the need of generating initial contour and setting
controlling parameters manually is proposed for medical image segmentation. The …

Accuracy and Clarity are important issues for medical imaging and same in the case of
segmentation. This paper proposes a novel method for segmentation of medical image …

Intensity inhomogeneities and different types/levels of image noise are the two major
obstacles to accurate image segmentation by region-based level set models. To provide a …