基于MRI的合成CT生成方法综述

doi:10.3969/j.issn.0258-8021.2020.04.012

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Abstract Radiation therapy is one of the important ways in tumor treatments,and CT is the main reference image of current radiation therapy. Compared with CT,MRI has good soft tissue contrast and is completely harmless to the human body. In recent years,MRI has been increasingly used for soft tissue delineation and radiation therapy guidance. However,the ionizing radiation of CT scan affects the health of patients,at the same time,scanning CT and MRI increase the economic burden of patients,and the registration fusion of CT and MRI introduces systematic errors.Radiotherapy using MRI only has received more and more attention from researchers. Nevertheless,MRI has no connection with electron density and cannot be directly used for dose calculation and X-ray based patient placement verification,therefore it is necessary to study the correlation algorithm to obtain the electron density information or HU value of the patient tissue according to the MRI image,that is to generate synthetic CT or pseudo CT. Currently existing methods for generating synthetic CT or pseudo CT are classified into three categories,including voxel-based,atlas-based and hybrid methods. According to the applied methods,we summarized and analyzed the sequence images,the number of applications and the anatomical parts. This study may represent a new direction in radiation therapy,which can avoid the use of ionizing radiation from traditional CT,and can use high-resolution MRI images to monitor tumors and enable patients to perform more precise radiation therapy.

Key words： radiotherapy magnetic resonance imaging (MRI) electron density synthetic CT or pseudo CT

Received: 19 September 2019

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R318

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	Jian Yingchao
	Fu Dongshan
	Wang Wei

Cite this article:

Jian Yingchao,Fu Dongshan,Wang Wei. A Review of MRI-Based Synthetic CT Image Generation[J]. Chinese Journal of Biomedical Engineering, 2020, 39(4): 485-492.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2020.04.012 OR http://cjbme.csbme.org/EN/Y2020/V39/I4/485

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