Tracing of Curvilinear Structures in 3D Images with Single Scale Diameter Measurement

Authors:
G. J. Streekstra;Arnold W. M. Smeulders;Rein van den Boomgaard
Affiliations:
-;-;-
Venue:
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Year:
1999

Citing 6
Cited 0

A surface specific-line tracking and slope recognition algorithm

Computer Vision, Graphics, and Image Processing
Vectorial tracking and directed contour finder for vascular network in digital subtraction angiography

Pattern Recognition Letters
Computer techniques in neuroanatomy

Computer techniques in neuroanatomy
An Unbiased Detector of Curvilinear Structures

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D and 3D medical images

CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Edge Detection and Ridge Detection with Automatic Scale Selection

CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)

Quantified Score

Hi-index	0.00

Visualization

Abstract

We introduce a 3D tracing method based on Differential geometry in Gaussian blurred images. The line point detection part of the tracing method starts with calculation of the line direction from the eigenvectors of the Hessian matrix. The sub-voxel center line position is estimated from a second order Taylor approximation of the 2D intensity profile perpendicular to the line. The line diameter is obtained at a single scale using the theoretical scale dependencies of the 0-th and 2nd order Gaussian derivatives at the line center. Experiments on synthetic images reveal that the localization of the centerline is mainly affected by line curvature. The diameter measurement is accurate for diameters as low as 4 voxels.