Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …

Featured Application This review provides a critical review of deep/machine learning
algorithms used in the identification of ischemic stroke and demyelinating brain diseases. It …

Image segmentation using a region-based active contour model could present difficulties
when its noise distribution is unknown. To overcome this problem, this paper proposes a …

With a good balance between tracking accuracy and speed, correlation filter (CF) has
become one of the best object tracking frameworks, based on which many successful …

It is still a challenging task to segment real-world images, since they are often distorted by
unknown noise and intensity inhomogeneity. To address these problems, we propose a …

Region-based active contour models are effective in segmenting images with poorly defined
boundaries but often fail when applied to images containing intensity inhomogeneity. The …

The active contour model is a widely used method for image segmentation. Most existing
active contour models yield poor performance when applied to images with severe intensity …

Variational Level Set (LS) has been a widely used method in medical segmentation.
However, it is limited when dealing with multi-instance objects in the real world. In addition …

Accurate image segmentation is an essential step in image analysis and understanding,
where active contour models play an important part. Due to the noise, low contrast and …

This paper presents a novel level set method for complex image segmentation, where the
local statistical analysis and global similarity measurement are both incorporated into the …