Medical image registration using unsupervised deep neural network: A scoping literature review

TL;DR

This paper provides a comprehensive scoping review of recent unsupervised deep neural network methods for medical image registration, highlighting advancements, applications, and future directions in this critical clinical area.

Contribution

It systematically summarizes the latest developments and applications of unsupervised deep learning techniques in medical image registration, offering insights into fundamental concepts and future research directions.

Findings

Recent unsupervised deep learning methods improve registration accuracy

Deep neural networks enable faster image registration processes

The review identifies key challenges and future trends in the field

Abstract

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.