Centerline optimization using vessel quantification model

Wenli Cai; Frank Dachille; Michael Meissner

doi:10.1117/12.594801

14 April 2005 Centerline optimization using vessel quantification model

Wenli Cai, Frank Dachille, Michael Meissner

Proceedings Volume 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images; (2005) https://doi.org/10.1117/12.594801
Event: Medical Imaging, 2005, San Diego, California, United States

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.

Citation Download Citation

Wenli Cai, Frank Dachille, and Michael Meissner "Centerline optimization using vessel quantification model", Proc. SPIE 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, (14 April 2005); https://doi.org/10.1117/12.594801

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