Level-set segmentation of noisy 3D images of numerically simulated blood vessels and vascular trees

M. Strzelecki, P. Szczypiński, A. Materka, M. Kociński, A. Sankowski
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引用次数: 6

Abstract

The objective of this paper is to evaluate performance of the level set approach applied to segmentation and tracking of noisy 3D images of computer-simulated blood-vessel phantoms and artificial vascular trees. Of particular interest was the segmentation of thin vessels, with diameter smaller that voxel size. Flood fill technique was also explored, for comparison. Quantitative measures of segmentation accuracy were used for the methods evaluation. It was demonstrated, that the level set method provides good segmentation results even for noisy images. This promising result encourages its future application for vascularity modeling based on MR images.
数值模拟血管和血管树三维噪声图像的水平集分割
本文的目的是评估水平集方法用于分割和跟踪计算机模拟血管幻影和人工血管树的噪声三维图像的性能。特别有趣的是细血管的分割,直径小于体素大小。还探讨了洪水填充技术,以供比较。采用定量的分割精度指标对方法进行评价。结果表明,水平集分割方法即使对噪声图像也能获得较好的分割效果。这一有希望的结果鼓励其未来应用于基于MR图像的血管建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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