领域(数学)
计算机科学
深度学习
观点
人工智能
图像配准
人工神经网络
钥匙(锁)
机器学习
无监督学习
图像(数学)
数据科学
计算机安全
数学
艺术
视觉艺术
纯数学
作者
Samaneh Abbasi,Meysam Tavakoli,Hamid Reza Boveiri,Mohammad Amin Mosleh-Shirazi,Raouf Khayami,Hedieh Khorasani,Reza Javidan,Alireza Mehdizadeh
标识
DOI:10.1016/j.bspc.2021.103444
摘要
In medicine, image registration is vital in image-guided interventions and other clinical applications. However, it is a difficult subject to be addressed which by the advent of machine learning, there have been considerable progress in algorithmic performance has recently been achieved for medical image registration in this area. The implementation of deep neural networks provides an opportunity for some medical applications such as conducting image registration in less time with high accuracy, playing a key role in countering tumors during the operation. The current study presents a comprehensive scoping review on the state-of-the-art literature of medical image registration studies based on unsupervised deep neural networks is conducted, encompassing all the related studies published in this field to this date. Here, we have tried to summarize the latest developments and applications of unsupervised deep learning-based registration methods in the medical field. Fundamental and main concepts, techniques, statistical analysis from different viewpoints, novelties, and future directions are elaborately discussed and conveyed in the current comprehensive scoping review. Besides, this review hopes to help those active readers, who are riveted by this field, achieve deep insight into this exciting field.
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