Improving the accuracy of the PET/MRI tridimensional multimodal rigid image registration based on the FATEMD

Q3 Computer Science Radioelectronic and Computer Systems Pub Date : 2023-03-07 DOI:10.32620/reks.2023.1.10
Abderazzak Taime, Aziz Khamjane, J. Riffi, H. Tairi
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Abstract

The subject matter of the article is the improvement in the accuracy of multimodal image registration between PET and MRI images in the medical field. The focus of the article pertains to the importance of these images in diagnosis, interpretation, and surgical intervention. This study increased the accuracy of PET/MRI multimodal image registration achieved through a new approach based on the multi-resolution image decomposition. The tasks to be solved are: The study proposes a new method, the fast and adaptive three-dimensional mode decomposition (FATEMD), to generate multi-resolution components for accurate registration. The method used: The study uses the FATEMD approach, which estimates the transformation parameters of the registration from the PET image and the residue of the second level of the MRI image that is obtained after the extraction of the first two tridimensional intrinsic mode functions (TIMFs). The following results were obtained: The proposed method of multimodal registration between PET and MRI images involves the use of the fast and adaptive three-dimensional mode decomposition (FATEMD) approach. This approach was tested on 25 pairs of images from the Vanderbilt database and was found to have improved accuracy compared to the usual method, as shown through comparative studies using measures of mutual information, normalized mutual information, and entropy correlation coefficient. Conclusion. The main objective achieved in the study was to enhance the accuracy of PET/MRI multimodal image registration through the application of the FATEMD decomposition method. This approach is novel compared to traditional methods as it involves estimating the transformation parameters from the PET image and the second level residue of the MRI image, resulting in more precise outcomes as opposed to using just the PET and MRI images alone. The integration of multiple imaging techniques, such as PET and MRI, provides healthcare professionals with a more comprehensive view of a patient's anatomy and physiology, leading to enhanced diagnosis and treatment planning.
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提高基于FATEMD的PET/MRI三维多模态刚性图像配准精度
本文的主题是提高医学领域PET和MRI图像之间的多模态图像配准精度。文章的重点是这些图像在诊断、解释和手术干预中的重要性。本研究通过一种基于多分辨率图像分解的新方法,提高了PET/MRI多模态图像配准的精度。本研究提出了一种新的方法——快速自适应三维模态分解(FATEMD),以生成多分辨率的精确配准分量。使用的方法:本研究采用FATEMD方法,从PET图像中估计配准的变换参数,提取前两个三维固有模态函数(timf)后得到MRI图像的第二级残差。本文提出的PET和MRI图像之间的多模态配准方法涉及使用快速和自适应三维模态分解(FATEMD)方法。该方法在Vanderbilt数据库的25对图像上进行了测试,通过使用互信息、归一化互信息和熵相关系数的度量进行比较研究,发现与通常的方法相比,该方法具有更高的准确性。结论。本研究的主要目的是通过应用FATEMD分解方法来提高PET/MRI多模态图像配准的准确性。与传统方法相比,这种方法是新颖的,因为它涉及到从PET图像和MRI图像的第二级残差中估计变换参数,与仅使用PET和MRI图像相比,产生更精确的结果。多种成像技术(如PET和MRI)的集成为医疗保健专业人员提供了更全面的患者解剖和生理视图,从而增强了诊断和治疗计划。
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来源期刊
Radioelectronic and Computer Systems
Radioelectronic and Computer Systems Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
3.60
自引率
0.00%
发文量
50
审稿时长
2 weeks
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