Biomedical image segmentation via constrained graph cuts and pre-segmentation
In this paper we present a high-fidelity method for 2D and 3D image boundary
segmentation. The algorithm is a novel combination of graph-cuts and initial image …
segmentation. The algorithm is a novel combination of graph-cuts and initial image …
Manual refinement system for graph-based segmentation results in the medical domain
The basic principle of graph-based approaches for image segmentation is to interpret an
image as a graph, where the nodes of the graph represent 2D pixels or 3D voxels of the …
image as a graph, where the nodes of the graph represent 2D pixels or 3D voxels of the …
3D medical image segmentation technique
SA El–said - International Journal of Biomedical …, 2015 - inderscienceonline.com
Despite continuing advances in mathematical models for automatic segmentation, many
medical practitioners still rely on 2D manual delineation, due to the lack of intuitive automatic …
medical practitioners still rely on 2D manual delineation, due to the lack of intuitive automatic …
Interactive organ segmentation using graph cuts
An N-dimensional image is divided into “object” and “background” segments using a graph
cut approach. A graph is formed by connecting all pairs of neighboring image pixels (voxels) …
cut approach. A graph is formed by connecting all pairs of neighboring image pixels (voxels) …
3D medical image segmentation approach based on multi-label front propagation
Many practical applications in the field of medical image processing require robust and valid
3D image segmentation results. In this paper, we present a semi-automatic iterative …
3D image segmentation results. In this paper, we present a semi-automatic iterative …
Graph cuts segmentation with statistical shape priors for medical images
J Zhu-Jacquot, R Zabih - 2007 Third International IEEE …, 2007 - ieeexplore.ieee.org
Segmentation of medical images is an important step in many clinical and diagnostic
imaging applications. Medical images present many challenges for automated segmentation …
imaging applications. Medical images present many challenges for automated segmentation …
A modified graph cuts image segmentation algorithm with adaptive shape constraints and its application to computed tomography images
H Chen, X Pan, X Lu, Q Xie - Biomedical signal processing and control, 2020 - Elsevier
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 …
and spleen, in abdominal computed tomography (CT) images hamper the machine-aided …
Multi-class regularization parameter learning for graph cut image segmentation
S Candemir, K Palaniappan… - 2013 IEEE 10th …, 2013 - ieeexplore.ieee.org
One of the first steps of computer-aided systems is robustly detect the anatomical
boundaries. Literature has several successful energy minimization based algorithms which …
boundaries. Literature has several successful energy minimization based algorithms which …
Image segmentation using normalized cuts and efficient graph-based segmentation
In this paper we propose an hybrid segmentation algorithm which incorporates the
advantages of the efficient graph based segmentation and normalized cuts partitioning …
advantages of the efficient graph based segmentation and normalized cuts partitioning …
A novel multi-stage 3D medical image segmentation: Methodology and validation
In this paper, we present a novel multi-stage algorithm for 3D medical image segmentation
that is inspired by an improved Fast Marching method and a morphological reconstruction …
that is inspired by an improved Fast Marching method and a morphological reconstruction …