INVESTIGATION OF AN ADAPTIVE REGULARIZATION PARAMETER SELECTION METHOD IN BIOLUMINESCENCE TOMOGRAPHY

被引:0
|
作者
Feng, Jinchao [1 ]
Yang, MingJie [1 ]
Jia, Kebin [1 ]
机构
[1] Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
基金
中国国家自然科学基金;
关键词
Bioluminescence tomography; automatic of regularization parameter; warm start; DIFFUSE OPTICAL TOMOGRAPHY; LOOKING; CURVE; LIGHT;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The regularization parameter plays a critical role in recovering bioluminescent source for regularization based reconstruction methods. To date, the regularization parameter is usually selected either through the empirical choice or prior experience of the user. Therefore, it is highly desirable to develop a methodology to adaptively determine the regularization parameter. In the paper, a deterministic algorithm for the selection of a regularization parameter has been applied for the first time to bioluminescence tomography (BLT). To improve the performance of the algorithm, a warm start strategy is introduced. Numerical experiments were performed to access the effectiveness of the proposed method.
引用
收藏
页码:181 / 184
页数:4
相关论文
共 50 条
  • [1] Adaptive parameter selection for Tikhonov regularization in Bioluminescence tomography
    Yu, Jingjing
    Liu, Fang
    He, Xiaowei
    Jiao, Licheng
    [J]. 2010 3RD INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2010), VOLS 1-7, 2010, : 86 - 90
  • [2] An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography
    Feng, Jinchao
    Qin, Chenghu
    Jia, Kebin
    Han, Dong
    Liu, Kai
    Zhu, Shouping
    Yang, Xin
    Tian, Jie
    [J]. MEDICAL PHYSICS, 2011, 38 (11) : 5933 - 5944
  • [3] Total variation regularization for bioluminescence tomography with an adaptive parameter choice approach
    Feng, Jinchao
    Jia, Xiaowei
    Jia, Kebin
    Qin, Chenghu
    Tian, Jie
    [J]. 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2011, : 3946 - 3949
  • [4] An adaptive Tikhonov regularization parameter choice method for electrical resistance tomography
    Xu, Yanbin
    Pei, Yang
    Dong, Feng
    [J]. FLOW MEASUREMENT AND INSTRUMENTATION, 2016, 50 : 1 - 12
  • [5] A Graph-guided Hybrid Regularization Method For Bioluminescence Tomography
    Chu, Mengxiang
    Guo, Hongbo
    He, Xuelei
    Wang, Beilei
    Liu, Yanqiu
    Hu, Xiangong
    Yu, Jingjing
    He, Xiaowei
    [J]. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2023, 230
  • [6] Adaptive regularization parameter selection method for enhancing generalization capability of neural networks
    Leung, CT
    Chow, TWS
    [J]. ARTIFICIAL INTELLIGENCE, 1999, 107 (02) : 347 - 356
  • [7] Total variation regularization for bioluminescence tomography with the split Bregman method
    Feng, Jinchao
    Qin, Chenghu
    Jia, Kebin
    Zhu, Shouping
    Liu, Kai
    Han, Dong
    Yang, Xin
    Gao, Quansheng
    Tian, Jie
    [J]. APPLIED OPTICS, 2012, 51 (19) : 4501 - 4512
  • [8] Lp Regularization for Bioluminescence Tomography Based on the Split Bregman Method
    Yifang Hu
    Jie Liu
    Chengcai Leng
    Yu An
    Shuang Zhang
    Kun Wang
    [J]. Molecular Imaging and Biology, 2016, 18 : 830 - 837
  • [9] Lp Regularization for Bioluminescence Tomography Based on the Split Bregman Method
    Hu, Yifang
    Liu, Jie
    Leng, Chengcai
    An, Yu
    Zhang, Shuang
    Wang, Kun
    [J]. MOLECULAR IMAGING AND BIOLOGY, 2016, 18 (06) : 830 - 837
  • [10] Sparse Regularization-Based Reconstruction for Bioluminescence Tomography Using a Multilevel Adaptive Finite Element Method
    He, Xiaowei
    Hou, Yanbin
    Chen, Duofang
    Jiang, Yuchuan
    Shen, Man
    Liu, Junting
    Zhang, Qitan
    Tian, Jie
    [J]. INTERNATIONAL JOURNAL OF BIOMEDICAL IMAGING, 2011, 2011