Medical images often exhibit intricate structures, inhomogeneous intensity, significant noise
and blurred edges, presenting challenges for medical image segmentation. Several …

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 …

A new region-based active contour model in level set formulation is proposed to segment
medical images with poorly defined boundaries. From literature, it is observed that the …

Anatomical objects in medical images very often have dual contours or surfaces that are
highly correlated. Manually segmenting both of them by following local image details is …

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 …

Level set methods have been widely used to implement active contours for image
segmentation applications due to their good boundary detection accuracy. In the context of …

Level set method is widely used for image segmentation. Recent work combined traditional
level set method with deep learning architecture for image segmentation. However, it is …

In the realm of computer vision, image segmentation has become a crucial task with
widespread applications, particularly in medical imaging. Although there have been …

A new level set method is proposed to segment medical images by introducing intensity
inhomogeneity and a double well potential function. First of all, an adaptive weighted …

The development of computer vision and medical treatment has driven the development of
the medical image. At the same time, as one of the key technologies of medical image …