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Vessel surface reconstruction with a tubular deformable model.

P J Yim¹, J J Cebral, R Mullick

¹Imaging Sciences Program, National Institutes of Health, Bethesda, MD 20892, USA. pyim@nih.gov

IEEE Transactions on Medical Imaging

|January 29, 2002

Summary

This study introduces a novel deformable model for reconstructing vessel surfaces from 3-D angiographic images, enabling objective measurement of atherosclerotic disease and stenosis.

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Area of Science:

Medical Imaging
Biomedical Engineering
Cardiovascular Research

Background:

Three-dimensional (3-D) angiography is increasingly used for evaluating atherosclerotic disease.
Accurate measurement of vessel stenosis from 3-D angiographic data is challenging due to limitations in image resolution and contrast.

Purpose of the Study:

To present a novel method for reconstructing vessel surfaces from 3-D angiographic data.
To enable objective and accurate measurement of vessel stenosis.

Main Methods:

A deformable model utilizing a tubular coordinate system was developed for vessel surface reconstruction.
Vertex merging was incorporated to ensure even vertex spacing and prevent surface self-intersection.
The method was validated using clinical magnetic resonance (MR) images of carotid and renal arteries, and physical and digital vascular phantoms.

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Main Results:

The deformable model demonstrated realistic and smooth surface reconstructions across all tested datasets.
Vessel radii measurements from the physical vascular phantom showed an error of less than 0.2 of the average voxel dimension.
Manual initialization variability had a negligible impact on stenosis measurements in the digital vascular phantom, with only one gross error in clinical images.

Conclusions:

The proposed deformable model provides an objective and accurate method for measuring vessel stenosis from 3-D angiographic images.
This technique overcomes limitations of current 3-D angiographic methods, offering improved evaluation of atherosclerotic disease.
The model's robustness and accuracy were validated across various imaging scenarios, suggesting its clinical utility.