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 |
ISSN | 2314-6133;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. |
DOI | 10.1155/2021/8824395 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000620154800007 |
出版者 | HINDAWI LTD |
引用统计 | |
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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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A New Robust Adaptiv(10041KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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