Share Email Print

Proceedings Paper

Centerline optimization using vessel quantification model
Author(s): Wenli Cai; Frank Dachille; Michael Meissner
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

An accurate and reproducible centerline is needed in many vascular applications, such as virtual angioscopy, vessel quantification, and surgery planning. This paper presents a progressive optimization algorithm to refine a centerline after it is extracted. A new centerline model definition is proposed that allows quantifiable minimum cross-sectional area. A centerline is divided into a number of segments. Each segment corresponds to a local generalized cylinder. A reference frame (cross-section) is set up at the center point of each cylinder. The position and the orientation of the cross-section are optimized within each cylinder by finding the minimum cross-sectional area. All local-optimized center points are approximated by a NURBS curve globally, and the curve is re-sampled to the refined set of center points. This refinement iteration, local optimization plus global approximation, converges to the optimal centerline, yielding a smooth and accurate central axis curve. The application discussed in this paper is vessel quantification and virtual angioscopy. However, the algorithm is a general centerline refinement method that can be applied to other applications that need accurate and reproducible centerlines.

Paper Details

Date Published: 14 April 2005
PDF: 8 pages
Proc. SPIE 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, (14 April 2005); doi: 10.1117/12.594801
Show Author Affiliations
Wenli Cai, Massschusetts General Hospital (United States)
Frank Dachille, Viatronix Inc. (United States)
Michael Meissner, Viatronix Inc. (United States)

Published in SPIE Proceedings Vol. 5746:
Medical Imaging 2005: Physiology, Function, and Structure from Medical Images
Amir A. Amini; Armando Manduca, Editor(s)

© SPIE. Terms of Use
Back to Top