Active contours, or snakes, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. A new type of external force for active contours, called gradient vector flow (GVF) was introduced recently to address problems associated with initialization and poor convergence to boundary concavities. GVF is computed as a diffusion of the gradient ...

BACKGROUND The purpose of this paper is to study the spatial agreement between visual field defects and ultra-wide field (UWF) fundus autofluorescence (FAF) in patients with birdshot chorioretinopathy (BSCR). The study is a retrospective, cross-sectional analysis of a university uveitis practice. Eight (8) eyes of five (5) patients with BSCR were included. Inclusion criteria were ability to fix...

Image segmentation is an important research area in Computer Vision and the GVF-snake is an effective segmentation algorithm presented in recent years. Traditional GVF-snake algorithm has a large capture range and can deal with boundary concavities. However, when interesting object has deep concavities, traditional GVF-snake algorithm can’t converge to true boundaries exactly. In this paper, a ...

An extension of the gradient vector flow snake (GVF snake) is presented. The method is based on combining two other external forces. First, the adaptive balloon force has been developed to increase the GVF snake’s capture range and convergence speed. Then, a dynamic GVF force is introduced to provide an efficient evolution-stop mechanism. In this way, we prevent the snake from breaking through ...

In this study, we discover some deficiencies of GVF and GGVF Snake such as it can not capture boundaries like “U” and “S” completely because of the counteraction of some external forces and the influence of the local minimum external forces. Based on analyzing force distribution rules of gradient vector flow, a standard is introduced to distinguish every control point is true or false. An addit...

Medical Image segmentation deals with segmentation of tumor in CT and MR images for improved quality in medical diagnosis. Geometric Vector Flow (GVF) enhances the concave object extraction capability. However, it suffers from high computational requirement and sensitiveness to noise. This paper intends to combine watershed algorithm with GVF snake model to reduce the computational complexity, ...

In this paper constrained Gradient Vector Flow (GVF) field generation is performed, for fast and accurate unsupervised stereoscopic semantic segmentation. The scheme utilizes the information provided by a depth segments map, produced by stereo analysis methods and incorporation of a segmentation algorithm. Then a Canny edge detector is applied to the depth region and produces an edge map. The e...

The medical CT images are irregular and have deep boundary concavities. So how to get the organ picture from serial images quickly and accurately is a difficult process. The paper discusses the shortcoming of GVF model being susceptible to structures with slender topology. For the better convergence we improve GVF model by setting the initial contour as the actual contour. The new algorithm com...

The Gradient Vector Flow (GVF) is a vector diffusion approach based on Partial Differential Equations (PDEs). This method has been applied together with snake models for boundary extraction medical images segmentation. The key idea is to use a diffusion-reaction PDE to generate a new external force field that makes snake models less sensitivity to initialization as well as improves the snake’s ...