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A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT
Zhou, Tao1,2; Lu, Huiling3; Hu, Fuyuan4; Shi, Hongbin5; Qiu, Shi6; Wang, Huiqun7
作者部门光谱成像技术研究室
2021-02-04
发表期刊BIOMED RESEARCH INTERNATIONAL
ISSN2314-6133;2314-6141
卷号2021
产权排序6
摘要

A new robust adaptive fusion method for double-modality medical image PET/CT is proposed according to the Piella framework. The algorithm consists of the following three steps. Firstly, the registered PET and CT images are decomposed using the nonsubsampled contourlet transform (NSCT). Secondly, in order to highlight the lesions of the low-frequency image, low-frequency components are fused by pulse-coupled neural network (PCNN) that has a higher sensitivity to featured area with low intensities. With regard to high-frequency subbands, the Gauss random matrix is used for compression measurements, histogram distance between the every two corresponding subblocks of high coefficient is employed as match measure, and regional energy is used as activity measure. The fusion factor d is then calculated by using the match measure and the activity measure. The high-frequency measurement value is fused according to the fusion factor, and high-frequency fusion image is reconstructed by using the orthogonal matching pursuit algorithm of the high-frequency measurement after fusion. Thirdly, the final image is acquired through the NSCT inverse transformation of the low-frequency fusion image and the reconstructed high-frequency fusion image. To validate the proposed algorithm, four comparative experiments were performed: comparative experiment with other image fusion algorithms, comparison of different activity measures, different match measures, and PET/CT fusion results of lung cancer (20 groups). The experimental results showed that the proposed algorithm could better retain and show the lesion information, and is superior to other fusion algorithms based on both the subjective and objective evaluations.

DOI10.1155/2021/8824395
收录类别SCI
语种英语
WOS记录号WOS:000620154800007
出版者HINDAWI LTD
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/94518
专题光谱成像技术研究室
通讯作者Zhou, Tao; Lu, Huiling
作者单位1.North Minzu Univ, Sch Comp Sci & Engn, Yinchuan 750021, Ningxia, Peoples R China
2.North Minzu Univ, Key Lab Images & Graph Intelligent Proc State Eth, Yinchuan 750021, Ningxia, Peoples R China
3.Ningxia Med Univ, Sch Sci, Yinchuan 750004, Ningxia, Peoples R China
4.Suzhou Univ Sci & Technol, Sch Elect & Informat Engn, Suzhou 215009, Peoples R China
5.Ningxia Med Univ, Dept Urol, Gen Hosp, Yinchuan 750004, Ningxia, Peoples R China
6.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian 710119, Peoples R China
7.Ningxia Med Univ, Sch Publ Hlth & Management, Yinchuan 750004, Ningxia, Peoples R China
推荐引用方式
GB/T 7714
Zhou, Tao,Lu, Huiling,Hu, Fuyuan,et al. A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT[J]. BIOMED RESEARCH INTERNATIONAL,2021,2021.
APA Zhou, Tao,Lu, Huiling,Hu, Fuyuan,Shi, Hongbin,Qiu, Shi,&Wang, Huiqun.(2021).A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT.BIOMED RESEARCH INTERNATIONAL,2021.
MLA Zhou, Tao,et al."A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT".BIOMED RESEARCH INTERNATIONAL 2021(2021).
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