The low contrast, blurred edges, and irregular contours of organs, such as the liver, kidney,
and spleen, in abdominal computed tomography (CT) images hamper the machine-aided …

Graph cut image partitioning is used to segment any type of the image data. The image data
is transformed by a kernel function so that the piecewise constant model of the graph cut …

Though graph cut based segmentation is a widely-used technique, it is known that
segmentation of a thin, elongated structure is challenging due to the “shrinking problem”. On …

Graph cut minimization formulates the image segmentation as a linear combination of
problem constraints. The salient constraints of the computer vision problems are data and …

This paper presents an effective combination of a statistical atlas-based approach and a
graph cuts algorithm for fully automated robust and accurate segmentation. Major …

The problem of interactive foreground/background segmentation in still images is of great
practical importance in image editing. They avoid the boundary-length bias of graph-cut …

Computer-aided segmentation of anatomical structures in medical images is a valuable tool
for efficient radiation therapy planning (RTP). As delineation errors highly affect the radiation …

Liver segmentation is an essential procedure in computer-assisted surgery, radiotherapy,
and volume measurement. It is still a challenging task to extract liver tissue from 3D CT …

A new proposed method of fully automatic processing frameworks is based on graph-cut
active contour algorithms. This paper addresses the problem of segmenting a liver and …

Abstract The Graph Cuts method of interactive segmentation has become very popular in
recent years. This method performs at interactive speeds for smaller images/volumes, but an …