Curvilinear structure detection and quantification is a large research area with many imaging
applications in fields such as biology, medicine, and engineering. Curvilinear enhancement …

Ridges are one of the key features of interest in areas such as computer vision and image
processing. Even though a significant amount of research has been directed to defining and …

Ridges and valleys are useful geometric features for image analysis. Different
characterizations have been proposed to formalize the intuitive notion of ridge/valley. In this …

Few published articles on curvilinear structures exist compared with works on detecting lines
or corners with high accuracy. In medical ultrasound imaging, the structures that need to be …

We propose the use of the second derivative of Anisotropic Gaussian Kernels for ridge
detection. Such kernels, which have proven successful in edge and corner detection, offer …

We propose a method for ridge detection at different widths using second-order Gaussian
derivative masks. The width of the ridge extracted varies depending on the mask size and its …

When computing descriptors of image data, the type of information that can be extracted may
be strongly dependent on the scales at which the image operators are applied. This article …

Reliable detection of surface creases defined via loci of the principal curvatures along their
corresponding curvature lines is important for many geometrical and graphical applications …

Understanding body part geometry is crucial for precise medical diagnostics. Curves
effectively describe anatomical structures and are widely used in medical imaging …

Finding the centerline and estimating the radius of linear structures is a critical first step in
many applications, ranging from road delineation in 2D aerial images to modeling blood …