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从单一受试者获取的多个医学图像的配准:为何、如何以及接下来做什么?

The registration of multiple medical images acquired from a single subject: why, how, what next?

作者信息

Little J A, Hawkes D J

机构信息

Division of Radiological Sciences, UMDS, Guy's Hospital, London, UK.

出版信息

Stat Methods Med Res. 1997 Sep;6(3):239-65. doi: 10.1177/096228029700600304.

Abstract

This paper reviews some of the recent techniques which have been used to register multiple images of the same patient. Image registration is a problem which has been receiving significant attention from the medical image processing community in recent years. A successful image registration can aid in patient diagnosis, treatment assessment, image guided interventions, surgery planning and surgery. At present the majority of work has focused on rigid body transformations of images. We shall discuss some of the approaches used and outline a key automatic method in detail. In order to allow image registration of parts of the body which do not remain rigid, either due to patient movement or a change in pathology, nonlinear deformation techniques are being developed. We shall talk of the history of these methods before explaining deformations using landmarks and a recent extension to allow the definition of rigid structures in such warps in more detail. Validation of these methods is of great importance and we shall discuss work which has already been carried out on this topic for rigid body registrations as well as ideas for the validation of deformation algorithms.

摘要

本文回顾了一些最近用于对同一患者的多幅图像进行配准的技术。图像配准是近年来医学图像处理领域备受关注的一个问题。成功的图像配准有助于患者诊断、治疗评估、图像引导干预、手术规划和手术。目前,大多数工作都集中在图像的刚体变换上。我们将讨论一些使用的方法,并详细概述一种关键的自动方法。为了实现对因患者移动或病理变化而不保持刚性的身体部位进行图像配准,正在开发非线性变形技术。在更详细地解释使用地标进行变形以及最近为在这种变形中定义刚性结构而进行的扩展之前,我们将先介绍这些方法的历史。这些方法的验证非常重要,我们将讨论已经在刚体配准这一主题上开展的工作以及变形算法验证的思路。

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