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数据冗余信息引导的低剂量心肌灌注CT成像方法

林嘉慧 边兆英 马建华 黄静 陶熙 曾栋 郭宏

南方医科大学学报2018,Vol.38Issue(1):27-33,7.
南方医科大学学报2018,Vol.38Issue(1):27-33,7.

数据冗余信息引导的低剂量心肌灌注CT成像方法

Redundancy information-induced image reconstruction for low-dose myocardial perfusion computed tomography

林嘉慧 1边兆英 1马建华 1黄静 1陶熙 1曾栋 1郭宏2

作者信息

  • 1. 南方医科大学生物医学工程学院//广州市医用放射成像与检测技术重点实验室,广东 广州 510515
  • 2. 天津医科大学总医院医学影像科,天津 300052
  • 折叠

摘要

Abstract

Objective In the clinic, myocardial perfusion computed tomography (MPCT) imaging is commonly used to detect and assess myocardial ischemia quantitatively. However, repeated scanning on the myocardial region in the cine mode will increase the radiation dose for patients. With lowering radiation dose, the quality of images are degraded by noise induced artifact, which hampers the diagnostic accuracy. Therefore, in this paper, we propose a redundancy information induced iterative reconstruction framework for high quality MPCT images at the case of low dose. Methods MPCT images have redundant structural information within frames and highly similarity between adjacent frames. Inspired by the two properties, in this work we propose a penalized weighted least-squares (PWLS) model incorporating NLM and TV based hybrid constraints, which is referred to as PWLS-aviNLM-TV for simplicity. The proposed algorithm can effectively eliminate noise and artifacts by taking into account the similarity between adjacent frames and redundancy information within frames, which also can improve spatial resolution within frames and maintain temporal resolution. Results The experimental results on the 4D extended cardiac-torso (XCAT) phantom and preclinical porcine dataset demonstrates that the PWLS-aviNLM-TV algorithm obtains better performance in terms of noise reduction and artifacts suppression than the PWLS-TV and PWLS-aviNLM algorithm. Moreover, the proposed algorithm can preserve the edges and detail information thereby efficiently differentiate ischemia from myocardium. Conclusion The present redundancy information induced reconstruction algorithm can reconstruct high-quality images from low-dose MPCT for better clinical imaging diagnosis.

关键词

低剂量/心肌灌注CT/非局部均值正则化/全变分正则化

Key words

low-dose/myocardial perfusion computed tomography/non-local means/total variation

引用本文复制引用

林嘉慧,边兆英,马建华,黄静,陶熙,曾栋,郭宏..数据冗余信息引导的低剂量心肌灌注CT成像方法[J].南方医科大学学报,2018,38(1):27-33,7.

基金项目

国家自然科学基金(U1708261,61701217,61571214, 81701690) (U1708261,61701217,61571214, 81701690)

广东省应用型科技研发专项(2015B020233008) (2015B020233008)

广州市科技计划项目(201705030009) Supported by National Natural Science Foundation of China (U1708261, 61701217, 61571214, 81701690). (201705030009)

南方医科大学学报

OA北大核心CSCDCSTPCDMEDLINE

1673-4254

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