Abstract

Fluorescence molecular tomography (FMT) is an important in vivo molecular imaging technique and has been widely studied in preclinical research. Many methods perform well in the reconstruction of a single fluorescent target but may fail in reconstructing multiple targets because of the severe ill-posedness of the FMT inverse problem. In this paper the original synchronization-inspired clustering algorithm (OSC) is introduced into FMT for resolving multiple targets from the reconstruction result. Based on OSC, a synchronization-based clustering algorithm for FMT (SC-FMT) is developed to further improve location accuracy. Both algorithms utilize the minimum spanning tree to automatically identify the number of the reconstructed targets without prior information and human intervention. A serial of numerical simulation results demonstrates that SC-FMT and OSC can resolve multiple targets robustly and automatically, which also shows the potential of the proposed postprocessing algorithms in FMT reconstruction.

© 2018 Optical Society of America

Three-way decision based reconstruction frame for fluorescence molecular tomography

Huangjian Yi, Pu Jiao, Xiaonan Li, Jinye Peng, and Xiaowei He
J. Opt. Soc. Am. A 35(11) 1814-1822 (2018)

Reconstruction algorithm for fluorescence molecular tomography using sorted L-one penalized estimation

Xiaowei He, Fang Dong, Jingjing Yu, Hongbo Guo, and Yuqing Hou
J. Opt. Soc. Am. A 32(11) 1928-1935 (2015)

Improved sparse reconstruction for fluorescence molecular tomography with L_1/2 regularization

Hongbo Guo, Jingjing Yu, Xiaowei He, Yuqing Hou, Fang Dong, and Shuling Zhang
Biomed. Opt. Express 6(5) 1648-1664 (2015)

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

Xia Cheng, Siyu Sun, Yinglong Xiao, Wenjing Li, Jintao Li, Jingjing Yu, and Hongbo Guo
J. Opt. Soc. Am. A 41(5) 844-851 (2024)

Multi-target reconstruction strategy based on blind source separation of surface measurement signals in FMT

Lizhi Zhang, Hongbo Guo, Jintao Li, Dizhen Kang, Diya Zhang, Xiaowei He, Yizhe Zhao, De Wei, and Jingjing Yu
Biomed. Opt. Express 14(3) 1159-1177 (2023)