Deep Learning in Medical Image Registration: A Review
It provides a comprehensive overview for researchers in medical imaging, but it is incremental as it synthesizes existing work without introducing new methods.
This paper reviews deep learning-based medical image registration methods, categorizing them into seven types and comparing their performance on lung and brain deformable registration using benchmark datasets.
This paper presents a review of deep learning (DL) based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into seven categories according to their methods, functions and popularity. A detailed review of each category was presented, highlighting important contributions and identifying specific challenges. A short assessment was presented following the detailed review of each category to summarize its achievements and future potentials. We provided a comprehensive comparison among DL-based methods for lung and brain deformable registration using benchmark datasets. Lastly, we analyzed the statistics of all the cited works from various aspects, revealing the popularity and future trend of development in medical image registration using deep learning.