Particle Swarm Optimization in 3D Medical Image Registration: A Systematic Review

IF 9.7 2区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Archives of Computational Methods in Engineering Pub Date : 2024-05-25 DOI:10.1007/s11831-024-10139-x

Lucia Ballerini

引用次数: 0

Abstract

Medical image registration seeks to find an optimal spatial transformation that best aligns the underlying anatomical structures. These problems usually require the optimization of a similarity metric. Swarm Intelligence techniques are very effective and efficient optimization methods. This systematic review focuses on 3D medical image registration using Particle Swarm Optimization.

Abstract Image

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三维医学影像配准中的粒子群优化：系统回顾

医学影像配准的目的是找到一种最佳空间变换，使底层解剖结构达到最佳配准。这些问题通常需要对相似度量进行优化。蜂群智能技术是非常有效和高效的优化方法。本系统综述重点介绍使用粒子群优化技术的三维医学图像配准。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Archives of Computational Methods in Engineering 工程技术-工程：综合

CiteScore

19.80

自引率

4.10%

发文量

153

审稿时长

>12 weeks

期刊介绍： Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.