Che Chengqian, Mathai Tejas Sudharshan, Galeotti John
Department of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA.
The Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA.
Methods. 2017 Feb 15;115:128-143. doi: 10.1016/j.ymeth.2016.12.006. Epub 2016 Dec 11.
This article is a review of registration algorithms for use between ultrasound images (monomodal image-based ultrasound registration). Ultrasound is safe, inexpensive, and real-time, providing many advantages for clinical and scientific use on both humans and animals, but ultrasound images are also notoriously noisy and subject to several unique artifacts/distortions. This paper introduces the topic and unique aspects of ultrasound-to-ultrasound image registration, providing a broad introduction and summary of the literature and the field. Both theoretical and practical aspects are introduced. The first half of the paper is theoretical, organized according to the basic components of a registration framework, namely preprocessing, image-similarity metrics, optimizers, etc. It further subdivides these methods between those suitable for elastic (non-rigid) vs. inelastic (matrix) transforms. The second half of the paper is organized by anatomy and is practical in nature, presenting and discussing the complete published systems that have been validated for registration in specific anatomic regions.
本文是一篇关于超声图像间配准算法(基于单模态图像的超声配准)的综述。超声具有安全、廉价且实时的特点,为人类和动物的临床及科研应用提供了诸多优势,但超声图像也因噪声大且存在多种独特伪像/畸变而臭名昭著。本文介绍了超声图像到超声图像配准的主题及独特之处,对相关文献和该领域进行了广泛的介绍与总结。文中既介绍了理论方面,也介绍了实践方面。论文的前半部分是理论性的,按照配准框架的基本组成部分进行组织,即预处理、图像相似性度量、优化器等。它还进一步将这些方法细分为适用于弹性(非刚性)变换与非弹性(矩阵)变换的方法。论文的后半部分按解剖结构进行组织,具有实践性质,展示并讨论了已在特定解剖区域配准中得到验证的完整的已发表系统。