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

## TL;DR

This paper systematically reviews the application of Particle Swarm Optimization (PSO) techniques for 3D medical image registration, highlighting their effectiveness in optimizing similarity metrics for aligning anatomical structures.

## Contribution

It provides a comprehensive overview of PSO-based methods in 3D medical image registration, emphasizing recent advancements and challenges.

## Key findings

- PSO methods improve registration accuracy in 3D medical imaging
- Enhanced convergence speed with hybrid PSO approaches
- Identification of key challenges in PSO application for medical images

## 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