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 …

Purpose The segmentation of organs and lesions from medical images is a challenging task
due to the presents of noise, intensity inhomogeneity, blurry/weak boundaries. In this paper …

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 …

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 …

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 …

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 …

Appropriate initialization and stable evolution are desirable criteria to satisfy in level set
methods. In this study, a novel region-based level set method utilizing both global and local …

Intensity inhomogeneity often appears in medical images, such as X-ray tomography and
magnetic resonance (MR) images, due to technical limitations or artifacts introduced by 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 …

In this paper, we present a new segmentation method using the level set framework for
medical volume images. The method was implemented using the surface evolution principle …