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用于磁共振血管造影(MRA)图像显示的最大强度投影算法的性能分析

Performance analysis of maximum intensity projection algorithm for display of MRA images.

作者信息

Sun Y, Parker D L

机构信息

Department of Electrical Engineering, City College of New York, NY 10031, USA.

出版信息

IEEE Trans Med Imaging. 1999 Dec;18(12):1154-69. doi: 10.1109/42.819325.

DOI:10.1109/42.819325
PMID:10695528
Abstract

The maximum intensity projection (MIP) is a popularly used algorithm for display of MRA images, but its performance has not been rigorously analyzed before. In this paper, four measures are proposed for the performance of the MIP algorithm and the quality of images projected from three-dimensional (3-D) data, which are vessel voxel projection probability, vessel detection probability, false vessel probability, and vessel-tissue contrast-to-noise ratio (CNR). As side products, vessel-missing probability, vessel receiver operating characteristics (ROC's), and mean number of false vessels are also studied. Based on the assumptions that the intensities of vessel, tissue, and noise along a projection path are independent Gaussian, these measures are derived and obtained all in closed forms. All the measures are functions of explicit parameters: vessel-to-tissue noise ratio (VTNR) and CNR of 3-D data prior to the MIP, vessel diameter, and projection length. It is shown that the MIP algorithm increases the CNR of large vessels whose CNR prior to the MIP is high and whose diameters are large. The increase in CNR increases with projection path length. On the other hand, all the proposed measures indicate that the small vessels that have low CNR prior to the MIP and small diameters suffer from the MIP. The performance gets worse as projection path length increases. All measures demonstrate a better performance when the vessel diameter is larger. Other properties and possible applications of the derived measures are also discussed.

摘要

最大强度投影(MIP)是一种常用于显示磁共振血管造影(MRA)图像的算法,但其性能此前尚未得到严格分析。本文针对MIP算法的性能以及从三维(3-D)数据投影得到的图像质量提出了四项指标,即血管体素投影概率、血管检测概率、伪血管概率以及血管-组织对比噪声比(CNR)。作为附带成果,还研究了血管漏检概率、血管接收者操作特征(ROC)以及伪血管的平均数量。基于沿投影路径的血管、组织和噪声强度为独立高斯分布的假设,推导出了这些指标,并且所有指标均以封闭形式得出。所有指标都是显式参数的函数:MIP之前3-D数据的血管-组织噪声比(VTNR)和CNR、血管直径以及投影长度。结果表明,MIP算法会提高MIP之前CNR较高且直径较大的大血管的CNR。CNR的增加随投影路径长度而增加。另一方面,所有提出的指标都表明,MIP之前CNR较低且直径较小的小血管会受到MIP的影响。随着投影路径长度增加,性能会变差。当血管直径较大时所有指标都显示出更好的性能。还讨论了推导指标的其他特性和可能的应用。

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