Darzi Fatemehzahra, Bocklitz Thomas
Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany.
Department of Photonic Data Science, Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany.
Bioengineering (Basel). 2024 Aug 2;11(8):786. doi: 10.3390/bioengineering11080786.
Medical image registration has become pivotal in recent years with the integration of various imaging modalities like X-ray, ultrasound, MRI, and CT scans, enabling comprehensive analysis and diagnosis of biological structures. This paper provides a comprehensive review of registration techniques for medical images, with an in-depth focus on 2D-2D image registration methods. While 3D registration is briefly touched upon, the primary emphasis remains on 2D techniques and their applications. This review covers registration techniques for diverse modalities, including unimodal, multimodal, interpatient, and intra-patient. The paper explores the challenges encountered in medical image registration, including geometric distortion, differences in image properties, outliers, and optimization convergence, and discusses their impact on registration accuracy and reliability. Strategies for addressing these challenges are highlighted, emphasizing the need for continual innovation and refinement of techniques to enhance the accuracy and reliability of medical image registration systems. The paper concludes by emphasizing the importance of accurate medical image registration in improving diagnosis.
近年来,随着X射线、超声、磁共振成像(MRI)和计算机断层扫描(CT)等各种成像模态的整合,医学图像配准已变得至关重要,它能够对生物结构进行全面分析和诊断。本文对医学图像配准技术进行了全面综述,深入聚焦于二维到二维(2D-2D)图像配准方法。虽然简要提及了三维配准,但主要重点仍在二维技术及其应用上。本综述涵盖了多种模态的配准技术,包括单模态、多模态、患者间和患者内配准。本文探讨了医学图像配准中遇到的挑战,包括几何畸变、图像特性差异、异常值和优化收敛,并讨论了它们对配准准确性和可靠性的影响。文中强调了应对这些挑战的策略,着重指出需要不断创新和改进技术,以提高医学图像配准系统的准确性和可靠性。本文最后强调了准确的医学图像配准在改善诊断方面的重要性。