Bioluminescence Tomography Based on Gaussian Weighted Laplace Prior Regularization for In Vivo Morphological Imaging of Glioma | |
Gao, Yuan1,4; Wang, Kun1; Jiang, Shixin2; Liu, Yuhao2; Ai, Ting3; Tian, Jie1,4 | |
刊名 | IEEE TRANSACTIONS ON MEDICAL IMAGING |
2017-11-01 | |
卷号 | 36期号:11页码:2343-2354 |
关键词 | Bioluminescence Tomography Multimodality Fusion Brain |
DOI | 10.1109/TMI.2017.2737661 |
文献子类 | Article |
英文摘要 | Bioluminescence tomography (BLT) is a powerful non-invasive molecular imaging tool for in vivo studies of glioma in mice. However, because of the light scattering and resulted ill-posed problems, it is challenging to develop a sufficient reconstruction method, which can accurately locate the tumor and define the tumor morphology in three-dimension. In this paper, we proposed a novel Gaussian weighted Laplace prior (GWLP) regularization method. It considered the variance of the bioluminescence energy between any two voxels inside an organ had a non-linear inverse relationship with their Gaussian distance to solve the over-smoothed tumor morphology in BLT reconstruction. We compared the GWLP with conventional Tikhonov and Laplace regularization methods through various numerical simulations and in vivo orthotopic glioma mouse model experiments. The in vivo magnetic resonance imaging and ex vivo green fluorescent protein images and hematoxylin-eosin stained images of whole head cryoslicing specimens were utilized as gold standards. The results demonstrated that GWLP achieved the highest accuracy in tumor localization and tumor morphology preservation. To the best of our knowledge, this is the first study that achieved such accurate BLT morphological reconstruction of orthotopic glioma without using any segmented tumor structure from any other structural imaging modalities as the prior for reconstruction guidance. This enabled BLT more suitable and practical for in vivo imaging of orthotopic glioma mouse models. |
WOS关键词 | FLUORESCENCE MOLECULAR TOMOGRAPHY ; RECONSTRUCTION METHOD ; OPTICAL TOMOGRAPHY ; LIGHT ; INFORMATION ; ALGORITHM ; MRI ; OPTIMIZATION ; SYSTEM ; REGION |
WOS研究方向 | Computer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging |
语种 | 英语 |
WOS记录号 | WOS:000414134200014 |
资助机构 | National Basic Research Program of China (973 Program)(2015CB755500) ; National Natural Science Foundation of China(81227901 ; CAS Youth Innovation Promotion Association(Y6S7021X51) ; 61671449 ; 81527805 ; 61231004 ; 61401462) |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/19557] |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 2.Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China 3.Southern Med Univ, Zhujiang Hosp, Dept Hepatobiliary Surg, Guangzhou 510280, Guangdong, Peoples R China 4.University of Chinese Academy of Sciences, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Gao, Yuan,Wang, Kun,Jiang, Shixin,et al. Bioluminescence Tomography Based on Gaussian Weighted Laplace Prior Regularization for In Vivo Morphological Imaging of Glioma[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2017,36(11):2343-2354. |
APA | Gao, Yuan,Wang, Kun,Jiang, Shixin,Liu, Yuhao,Ai, Ting,&Tian, Jie.(2017).Bioluminescence Tomography Based on Gaussian Weighted Laplace Prior Regularization for In Vivo Morphological Imaging of Glioma.IEEE TRANSACTIONS ON MEDICAL IMAGING,36(11),2343-2354. |
MLA | Gao, Yuan,et al."Bioluminescence Tomography Based on Gaussian Weighted Laplace Prior Regularization for In Vivo Morphological Imaging of Glioma".IEEE TRANSACTIONS ON MEDICAL IMAGING 36.11(2017):2343-2354. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论