Abstract
This document describes an ITK implementation of an interactive method for tracing curvilinear structures. The basic tools provided in this framework are an oriented flux-based tubularity measure and a geodesic path tracer that uses the fast marching algorithm. The framework is efficient and requires minimal user interaction to trace curvilinear structures such as vessels and neurites in 2D images and 3D image stacks.
Highlights
We deal with the problem of finding a complete segmentation of curvilinear structures in 2D images and 3D stacks
We use a variant of the minimal path method applied in the scale-space domain [4]
The geodesic path is computed by back-propagating from an end point to the start
Summary
We deal with the problem of finding a complete segmentation of curvilinear structures in 2D images and 3D stacks. Given an N-D image, this creates an (N+1)-D scale-space tubularity measure, which, in this work, is taken as the sum of the two dominant eigenvalues of the Optimally Oriented Flux (OOF) matrix [3]. This step is followed by computing a distance map from a given start point using the Fast Marching Algorithm [6]. By incorporating an extra non-spatial dimension into the search space, the method models a tubular path in a 3D image as a sequence of 4D points (three spatial dimensions for image coordinates and a scale dimension that quantifies curvilinear structure thickness). We describe our implementation of the oriented flux measure and the tubular geodesic method
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