Section of Biomedical Image Analysis, Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
IEEE Trans Med Imaging. 2013 Jul;32(7):1153-90. doi: 10.1109/TMI.2013.2265603. Epub 2013 May 31.
Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.
形变图像配准是医学图像处理中的一项基本任务。在其最重要的应用中，人们可能会引用：1）多模态融合，其中通过不同的成像设备或协议获取的信息被融合以促进诊断和治疗计划；2）纵向研究，其中研究时间结构或解剖结构的变化；3）群体建模和统计图谱，用于研究正常解剖学的可变性。在本文中，我们试图概述形变配准方法，重点介绍该领域的最新进展。此外，还强调了应用于医学图像的技术。为了深入研究图像配准方法，我们将其主要组件独立地进行了识别和研究。最近的技术以系统的方式呈现。本文的贡献是以系统的方式提供对配准技术的广泛描述。
