Fluorescence molecular tomography based on an online maximum a posteriori estimation algorithm

被引:0
|
作者
Cheng, Xia [1 ]
Sun, Siyu [1 ]
Xiao, Yinglong [1 ]
Li, Wenjing [1 ]
Li, Jintao [2 ]
Yu, Jingjing [1 ]
Guo, Hongbo [2 ]
机构
[1] Shaanxi Normal Univ, Sch Phys & Informat Technol, Xian 710119, Peoples R China
[2] Northwest Univ, Sch Informat Sci & Technol, Xian 710069, Peoples R China
基金
中国国家自然科学基金;
关键词
BIOLUMINESCENCE TOMOGRAPHY; RECONSTRUCTION ALGORITHM; SPARSE RECONSTRUCTION;
D O I
10.1364/JOSAA.519667
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Fluorescence molecular tomography (FMT) is a non-invasive, radiation -free, and highly sensitive optical molecular imaging technique for early tumor detection. However, inadequate measurement information along with significant scattering of near -infrared light within the tissue leads to high ill-posedness in the inverse problem of FMT. To improve the quality and efficiency of FMT reconstruction, we build a reconstruction model based on log -sum regularization and introduce an online maximum a posteriori estimation (OPE) algorithm to solve the non -convex optimization problem. The OPE algorithm approximates a stationary point by evaluating the gradient of the objective function at each iteration, and its notable strength lies in the remarkable speed of convergence. The results of simulations and experiments demonstrate that the OPE algorithm ensures good reconstruction quality and exhibits outstanding performance in terms of reconstruction efficiency. (c) 2024 Optica Publishing Group
引用
收藏
页码:844 / 851
页数:8
相关论文
共 50 条
  • [41] Robust Online Multi-object Tracking by Maximum a Posteriori Estimation with Sequential Trajectory Prior
    Yang, Min
    Pei, Mingtao
    Shen, Jiajun
    Jia, Yunde
    NEURAL INFORMATION PROCESSING, PT I, 2015, 9489 : 623 - 633
  • [42] MAXIMUM A POSTERIORI ESTIMATION OF POSITION IN SCINTILLATION CAMERAS
    GRAY, RM
    MACOVSKI, A
    IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 1976, 23 (01) : 849 - 852
  • [43] Reconstruction algorithm for fluorescence molecular tomography using sorted L-one penalized estimation
    He, Xiaowei
    Dong, Fang
    Yu, Jingjing
    Guo, Hongbo
    Hou, Yuqing
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2015, 32 (11) : 1928 - 1935
  • [44] Maximum a Posteriori Estimation for Information Source Detection
    Chang, Biao
    Chen, Enhong
    Zhu, Feida
    Liu, Qi
    Xu, Tong
    Wang, Zhefeng
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 50 (06): : 2242 - 2256
  • [45] Maximum a posteriori height estimation in InSAR imaging
    Ferraiuolo, G
    Pascazio, V
    Schirinzi, G
    IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS: REMOTE SENSING: INTEGRATING OUR VIEW OF THE PLANET, 2002, : 1732 - 1734
  • [46] MAXIMUM A POSTERIORI ESTIMATION OF ROOM IMPULSE RESPONSES
    Florencio, Dinei
    Zhang, Zhengyou
    2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 728 - 732
  • [47] Maximum a Posteriori Estimation of Dynamically Changing Distributions
    Volkhardt, Michael
    Kalesse, Soeren
    Mueller, Steffen
    Gross, Horst-Michael
    KI 2009: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2009, 5803 : 484 - 491
  • [48] Spatial correlated maximum a posteriori adaptation algorithm
    Yu, P
    Wang, ZY
    CHINESE JOURNAL OF ELECTRONICS, 2002, 11 (03): : 336 - 340
  • [49] MAP estimation with structural priors for fluorescence molecular tomography
    Zhang, Guanglei
    Cao, Xu
    Zhang, Bin
    Liu, Fei
    Luo, Jianwen
    Bai, Jing
    PHYSICS IN MEDICINE AND BIOLOGY, 2013, 58 (02): : 351 - 372
  • [50] An Optimized Algorithm Maximum A Posteriori Energy Detection
    Arora, Kirti
    Singal, T. L.
    2015 FIFTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT2015), 2015, : 359 - 363