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基于可调双向量参数的SPECT重建数据伪彩色映射模型
引用本文:孙裕洋,姜涵,郑永果,陈明,胡效坤,李刚.基于可调双向量参数的SPECT重建数据伪彩色映射模型[J].CT理论与应用研究,2021,30(6):701-708.
作者姓名:孙裕洋  姜涵  郑永果  陈明  胡效坤  李刚
作者单位:1. 山东科技大学 a) 计算机科学与工程学院;b) 数学与系统科学学院, 山东 青岛 266590;
基金项目:国家重点研发计划(脑胶质瘤碘-125精准治疗体系及关键技术的研究与推广(2019YFE0120100));山东省自然科学基金(面向煤岩三维微观信息表征的能谱CT成像方法研究(R2020MF016);单源双探截断式的骨骼CT成像方法研究(ZR202102220343))。
摘    要:SPECT是对植入患者体内的放射性粒子发射的γ射线进行成像,其图像中灰度信息反映了γ射线的计数值,变换后相应于射线剂量值。临床中通常为了观察剂量在病灶附近的分布情况,需要将SPECT图像进行伪彩色处理,再与CT图像进行融合。但是,SPECT/CT常用的处理软件中伪彩色处理很难提供足够的剂量细节分辨,难以满足临床诊疗的需求。针对脑部肿瘤治疗中对γ射线剂量分布细节的需求,本文基于SPECT的DICOM数据,提出一种含有可调双向量参数的伪彩色映射显示模型,创建多层次的映射关系。该方法不仅可以控制伪彩色显示区域还可以调整剂量显示的多分段细节。Python的数值实验结果表明,本文所提伪彩色映射模型和算法能够更加清晰、准确地显示SPECT图像中感兴趣的剂量区域和数据范围,与CT图像融合后可明显增强SPECT/CT的病灶区域和剂量分布层次感,精准显示病灶部位的粒子空间和放射剂量分布信息,为临床疗效的判定提供可靠依据。 

关 键 词:伪彩色映射    SPECT图像    放射性粒子    γ射线剂量分布
收稿时间:2021-08-22

The Pseudo-color Mapping Model of Spect Reconstruction Data Based on Adjustable Dual-vector Parameters
Affiliation:1. a) College of Computer Science and Engineering;b) College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China;2. Department of Interventional Radiology, the Affiliated Hospital of Qingdao University, Qingdao 266555, China
Abstract:SPECT performs imaging on the γ-ray emitted by radioactive particles implanted in the patient's body. The gray information of SPECT image represents counts of γ-ray, which can correspond to the radiation dose value of γ-ray after transformation. In order to observe the dose distribution near the lesion clinically, it is necessary to perform pseudo-color processing on SPECT images, which are then fused with CT images. However, the SPECT/CT pseudo-color processing of conventional processing software is difficult to provide sufficient dose detail resolution, which cannot meet the needs of clinical diagnosis and treatment. For the requirement of γ radiation dose distribution details in the treatment of brain tumors, we present a pseudo-color mapping model with adjustable dual-vector parameters, which is based on DICOM data of SPECT imaging and can bulid a multi-level mapping relationship.The proposed method can not only control the pseudo-color display area, but also adjust the multi-segment details of the dose display. Results of numerical experiments by Python show that the proposed mapping method can display the dose area and data range of interest in SPECT images more clearly and accurately. After being fused with the CT image, they can significantly enhance the layering of dose distribution in the SPECT/CT focus area,, and accurately display the information of particle space and radiation dose distribution. The proposed method can provide a reliable basis for the judgment of clinical efficacy. 
Keywords:
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