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肝脏对比增强磁共振 3D 灌注时间序列图像配准评估。

Evaluation of the registration of temporal series of contrast-enhanced perfusion magnetic resonance 3D images of the liver.

机构信息

Department of Informatics, University of Valencia, Avda. de la Universidad, s/n 46100-Burjasot, Valencia, Spain.

出版信息

Comput Methods Programs Biomed. 2012 Dec;108(3):932-45. doi: 10.1016/j.cmpb.2012.04.015. Epub 2012 Jun 15.

Abstract

The registration of 2D and 3D images is one of the key tasks in medical image processing and analysis. Accurate registration is a crucial preprocessing step for many tasks; consequently, the evaluation of its accuracy becomes necessary. Unfortunately, this is a difficult task, especially when no golden pattern (true result) is available and when the signal values may have changed between successive images to be registered. This is the case this paper deals with: we have a series of 3D images, magnetic resonance images (MRI) of the liver and adjacent areas that have to be registered. They have been taken while a contrast is diffused through the liver tissue, so intensity of each observed point changes for two reasons: contrast diffusion/perfusion and deformation of the liver (due to body movement and breathing). In this paper, we introduce a new method to automatically compare two or more registration algorithms applied to the same case of a perfusion magnetic resonance dynamic image so that the best of them can be chosen when no ground truth is available. This is done by modeling the function that gives the intensity at a given point as a functional datum, and using statistical techniques to assess its change in comparison with other functions. An example of the application is shown by comparing two parametrizations of a B-spline based registration algorithm. The main result of the proposed method is a suggestive evidence to guide the physician in the process of selecting a registration algorithm, that recommends the algorithm of minimal complexity but still suitable for the case to be analyzed.

摘要

2D 和 3D 图像的配准是医学图像处理和分析中的关键任务之一。准确的配准是许多任务的关键预处理步骤;因此,评估其准确性变得必要。不幸的是,这是一项困难的任务,特别是当没有黄金模式(真实结果)可用,并且信号值在要注册的连续图像之间可能已经改变时。本文就是处理这种情况的:我们有一系列的 3D 图像,肝脏及其相邻区域的磁共振图像(MRI)需要进行配准。这些图像是在对比剂扩散通过肝组织时拍摄的,因此每个观察点的强度由于两个原因而发生变化:对比剂的扩散/灌注以及肝脏的变形(由于身体运动和呼吸)。在本文中,我们介绍了一种新方法,用于自动比较应用于相同灌注磁共振动态图像的同一案例的两种或更多种配准算法,以便在没有真实情况时可以选择最佳算法。这是通过将在给定点给出强度的函数建模为函数基准,并使用统计技术来评估与其他函数相比其变化来实现的。通过比较基于 B 样条的配准算法的两种参数化,展示了一个应用示例。所提出方法的主要结果是为医生提供了选择配准算法的建议,推荐了复杂度最小但仍适合要分析的案例的算法。

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