Convolutional neural networks (CNNs) have achieved state-of-the-art performance for
automatic medical image segmentation. However, they have not demonstrated sufficiently …

A computer-implemented method for segmenting an input image, the method comprises:
generating a first segmentation of the input image using a first machine learning system, the …

This paper presents a comparative study using different color spaces to evaluate the
performance of color image segmentation using the automatic GrabCut technique. GrabCut …

As an emerging modality for whole breast imaging, ultrasound tomography (UST), has been
adopted for diagnostic purposes. Efficient segmentation of an entire breast in UST images …

An interactive method for segmentation and isosurface extraction of medical volume data is
proposed. In conventional methods, users decompose a volume into multiple regions …

GrabCut is one of the most powerful semi-automatic segmentation techniques. One main
drawback of GrabCut is the need for user interaction in order to initialize the segmentation …

This paper proposes a new technique for the problem of color image segmentation using
GrabCut. GrabCut is considered as one of the semi-automatic segmentation techniques …

Foreground segmentation enables dynamic reconstruction of the moving objects in static
scenes. After KinectFusion had proposed a novel method that constructs the foreground …

GrabCut is one of the powerful color image segmentation techniques. One main
disadvantage of GrabCut is the need for initial user interaction to initialize the segmentation …

In this paper, we modified GrabCut for gray-scale slice-stacked medical image
segmentation. First, GrabCut was extended from planar to volume image processing …