Fast delineation and visualization of vessels in 3-D angiographic images

Abstract

A method is presented which aids the clinician in obtaining quantitative measures and a three-dimensional (3-D) representation of vessels from 3-D angiographic data with a minimum of user interaction. Based on two user defined starting points, an iterative procedure tracks the central vessel axis. During the tracking process, the minimum diameter and a surface rendering of the vessels are computed, allowing for interactive inspection of the vasculature. Applications of the method to CTA, contrast enhanced (CE)-MRA and phase contrast (PC)-MRA images of the abdomen are shown. In all applications, a long stretch of vessels with varying width is tracked, delineated, and visualized, in less than 10 s on a standard clinical workstation.

A non-parametric vessel detection method for complex vascular structures

“…Different minimum cost path techniques [3,10,18,20] provide automatic and robust vessel centerline extraction for vascular analysis after segmentation. Skeleton-based vascular segmentation algorithms [1,35,38] were also proposed for both size measurement and the connectivity analysis simultaneously. In most of these methods, they integrate the results from the aforementioned feature extraction methods, which are inadequate at branching points.…”

Design and study of flux-based features for 3D vascular tracking

“…From the flux point of view, regularization is considered as preprocessing of the gradient vector field and is not necessarily performed by Gaussian filtering. In [8,9,10,11], the Gaussian standard deviation varies with the targeted vessel radius, following principles of Gaussian linear scale-space theory. Regularization induces a tradeoff between detection robustness and discriminative power [11].…”

“…In [9,10], Gaussian-smoothed gradient vectors are also projected on radial directions. The core feature from [11] computes Gaussian derivatives oriented along radial rays, which is theoretically equivalent to the projection method from a continuous point of view.…”

Accurate Quantification of Small-Diameter Tubular Structures in Isotropic CT Volume Data Based on Multiscale Line Filter Responses

“…A typical method is to extract medial axes of the structures and then quantitate the width of the contour of cross-section orthogonal to the axis [1], [2], [3]. The diameters of small-diameter structures are known to be overestimated when they are measured based on the cross-sectional contours [3].…”