Czajkowski Paweł, Piotrowski Tomasz
Department of Medical Physics, Gdynia Oncology Centre, Gdynia, Poland.
Department of Electroradiology, Poznan University of Medical Sciences, Poznan, Poland.
Rep Pract Oncol Radiother. 2019 Jan-Feb;24(1):28-34. doi: 10.1016/j.rpor.2018.09.004. Epub 2018 Oct 10.
The aim of this study is to present a short and comprehensive review of the methods of medical image registration, their conditions and applications in radiotherapy. A particular focus was placed on the methods of deformable image registration.
To structure and deepen the knowledge on medical image registration in radiotherapy, a medical literature analysis was made using the Google Scholar browser and the medical database of the PubMed library.
Chronological review of image registration methods in radiotherapy based on 34 selected articles. A particular attention was given to show: (i) potential regions of the application of different methods of registration, (ii) mathematical basis of the deformable methods and (iii) the methods of quality control for the registration process.
The primary aim of the medical image registration process is to connect the contents of images. What we want to achieve is a complementary or extended knowledge that can be used for more precise localisation of pathogenic lesions and continuous improvement of patient treatment. Therefore, the choice of imaging mode is dependent on the type of clinical study. It is impossible to visualise all anatomical details or functional changes using a single modality machine. Therefore, fusion of various modality images is of great clinical relevance. A natural problem in analysing the fusion of medical images is geographical errors related to displacement. The registered images are performed not at the same time and, very often, at different respiratory phases.
本研究旨在对医学图像配准方法及其在放射治疗中的条件和应用进行简短而全面的综述。特别关注了可变形图像配准方法。
为了构建和深化放射治疗中医学图像配准的知识,使用谷歌学术浏览器和PubMed库的医学数据库进行了医学文献分析。
基于34篇选定文章对放射治疗中图像配准方法进行了按时间顺序的综述。特别关注展示:(i)不同配准方法的潜在应用领域,(ii)可变形方法的数学基础,以及(iii)配准过程的质量控制方法。
医学图像配准过程的主要目的是连接图像内容。我们想要实现的是一种互补或扩展的知识,可用于更精确地定位致病病变并不断改进患者治疗。因此,成像模式的选择取决于临床研究的类型。使用单一模态机器不可能可视化所有解剖细节或功能变化。因此,各种模态图像的融合具有重要的临床意义。分析医学图像融合时的一个自然问题是与位移相关的地理误差。配准的图像不是在同一时间进行的,而且经常处于不同的呼吸阶段。