Journal of Mathematical Imaging and Vision
Shape-Based Mutual Segmentation
International Journal of Computer Vision
Anisotropic Haralick Edge Detection Scheme with Application to Vessel Segmentation
MIAR '08 Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality
R-PLUS: A Riemannian Anisotropic Edge Detection Scheme for Vascular Segmentation
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
A Statistical Overlap Prior for Variational Image Segmentation
International Journal of Computer Vision
Appearance and Shape Prior Alignments in Level Set Segmentation
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
International Journal of Computer Vision
A Combinatorial Method for Topology Adaptations in 3D Deformable Models
International Journal of Computer Vision
Piecewise constant level set method for 3D image segmentation
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
A modified support vector machine and its application to image segmentation
Image and Vision Computing
Tubular Structure Segmentation Based on Minimal Path Method and Anisotropic Enhancement
International Journal of Computer Vision
Automatic segmentation of human facial tissue by MRI-CT fusion: A feasibility study
Computer Methods and Programs in Biomedicine
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Hi-index | 0.01 |
We present a new segmentation method for extracting thin structures embedded in three-dimensional medical images based on modern variational principles. We demonstrate the importance of the edge alignment and homogeneity terms in the segmentation of blood vessels and vascular trees. For that goal, the Chan-Vese minimal variance method is combined with the boundary alignment, and the geodesic active surface models. An efficient numerical scheme is proposed. In order to simultaneously detect a number of different objects in the image, a hierarchal approach is applied.